Infrared analysis of benign tumors

ABSTRACT

A method including identifying a subject as possibly having a benign tumor in ovarian tissue and obtaining an infrared spectrum of a PBMC sample of the subject and assessing a characteristic of the sample at at least one wavenumber selected from the group consisting of: 754.0±4 cm-1, 1103.6±4 cm-1, 1121.4±4 cm-1, 1346.1±4 cm-1, 1376.9±4 cm-1, 753.50±4 cm-1, 850.5±4 cm-1, 918.9±4 cm-1, 1058.7±4 cm-1, 1187.9±4 cm-1 and 1651.7±4 cm-1. Using a processor comparing, at the at least one wavenumber, the infrared spectrum to an infrared spectrum obtained from a PBMC sample from a person without a benign tumor, to detect a difference between the infrared spectrum of the PBMC sample of the subject and the infrared spectrum obtained from the PBMC sample from the person without a benign tumor. Other applications are also described.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application is a continuation application of U.S. Ser. No.14/894,128 to Kapelushnik et al., which issued as U.S. Pat. No.9,804,145 and which is the US national phase of PCT Application no.PCT/IL2013/050945 to Kapelushnik et al., filed Nov. 14, 2013, publishedas WO 2014/191980 to Kapelushnik et al., and claims the priority of U.S.Provisional Patent Application No. 61/827,933, entitled “Differentialdiagnosis of benign tumors,” filed May 28, 2013, which is incorporatedherein by reference.

FIELD OF EMBODIMENTS OF THE INVENTION

Embodiments of the present invention relate generally to diagnosis oftumors, and particularly to methods for differential diagnosis of benignand malignant solid tumors.

BACKGROUND

Infrared spectroscopy is a technique based on the absorption orreflection of infrared radiation by chemical substances, each chemicalsubstance having unique absorption spectra. Fourier Transform Infrared(FTIR) spectroscopy is used to identify biochemical compounds andexamine the biochemical composition of a biological sample. Typically,FTIR spectra are composed of several absorption bands each correspondingto specific functional groups related to cellular components such aslipids, proteins, carbohydrates and nucleic acids. Processes such ascarcinogenesis may trigger global changes in cancer cell biochemistry,resulting in differences in the absorption spectra when analyzed by FTIRspectroscopy techniques. Therefore, FTIR spectroscopy is commonly usedto distinguish between normal and abnormal tissue by analyzing thechanges in absorption bands of macromolecules such as lipids, proteins,carbohydrates and nucleic acids. Additionally, FTIR spectroscopy may beutilized for evaluation of cell death mode, cell cycle progression andthe degree of maturation of hematopoietic cells.

Analysis of certain markers (e.g., certain proteins, peptides, RNAmolecules) in a patient's circulation may be useful in detection and/ormonitoring of cancer. For example, studies have shown that analysis of apatient's blood plasma for certain oncofetal antigens, enzymes and/ormiRNA molecules may assist in diagnosis and prognosis of certain typesof cancer. FTIR spectroscopy is used for analysis of various compoundsin blood plasma such as total proteins, creatinine, amino acids, fattyacids, albumin, glucose, fibrinogen, lactate, triglycerides, glycerol,urea, cholesterol, apolipoprotein and immunoglobulin.

SUMMARY OF EMBODIMENTS OF THE INVENTION

In some applications of the present invention, a method and system areprovided for the differential diagnosis of pre-malignant, malignant, andbenign tumors. Accordingly, some applications of the present inventionallow distinguishing between subjects suffering from a pre-malignant ora malignant condition and subjects with a benign, non-malignant tumor.

Some applications of the present invention provide a method comprisingobtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample of a subject by analyzing the sample by infraredspectroscopy; and based on the infrared spectrum, generating an outputindicative of the presence of a benign tumor of the subject.

Additionally or alternatively, some applications of the presentinvention provide a method comprising obtaining an infrared (IR)spectrum of a plasma sample of a subject by analyzing the sample byinfrared spectroscopy; and based on the infrared spectrum, generating anoutput indicative of the presence of a benign tumor of the subject.

Typically, analysis by infrared (IR) spectroscopy, e.g., FTIRspectroscopy and microspectroscopy (FTIR MSP), of global biochemicalproperties of blood-derived mononuclear cells or plasma can indicate thepresence of a malignant and pre-malignant condition or a benign tumor.In accordance with some applications of the present invention,experiments were carried out in which PBMC or plasma samples from aplurality of subjects having either benign solid tumors or malignant andpre-malignant solid tumors (for example, but not limited to, tumors inbreast tissue, gynecological tissues or gastrointestinal tract tissue)were analyzed by FTIR microspectroscopy techniques. Subsequently, theFTLR spectra (absorption and/or reflection) of the PBMC or plasmasamples of the subjects with benign tumors were compared to the FTIRspectra of PBMC or plasma samples obtained from the cancer patients andto the FTIR spectra of PBMC or plasma samples obtained from a controlgroup. The control group comprised healthy subjects who did not haveidentified pre-malignant, malignant or benign tumors.

The inventors have identified that the PBMC or plasma samples obtainedfrom patients suffering from a pre-malignant or malignant solid tumorproduce FTIR spectra that differ from those of the control group who donot suffer from a malignant solid tumor, allowing distinguishing betweenthe cancer patients and controls. Furthermore, the inventors haveidentified that the PBMC or plasma samples obtained from subjects with abenign tumor produce FTIR spectra that differ from those of the cancerpatients and those of the control group, allowing distinguishing betweensubjects with benign tumors, cancer patients and healthy individuals.Thus, some applications of the present invention can be used to diagnosecancer patients suffering from solid tumors and to distinguish a subjectwith a benign tumor from a cancer patient and a healthy subject. Thedistinction by FTIR spectroscopy between controls and subjects sufferingfrom either benign or pre-malignant and malignant tumors is typicallyperformed based on analysis of PBMC and blood plasma samples and not ofthe actual tumor cells, allowing broad population screening ifappropriate, and reducing the need in many cases for performing a tissuebiopsy.

For some applications, a data processor analyzes the IR spectrum, e.g.,the FTIR spectrum, of the PBMC or plasma sample of the subject.Information from the data processor is typically fed into an output unitthat generates a result indicative of the presence of a benign tumorand/or a pre-malignant or malignant condition, based on the infrared(IR) spectrum. Additionally, the data processor is typically configuredto calculate a second derivative of the infrared (IR) spectrum of thePBMC sample and, based on the second derivative of the infrared (IR)spectrum, to generate an output indicative of the presence of a benign,pre-malignant or malignant tumor.

For some applications, analysis by IR spectroscopy, e.g., FTIRspectroscopy, of the biochemistry of PBMC, plasma or any otherblood-derived cells is used for the screening of large populations,aiding in the early detection of solid tumors. Additionally oralternatively, applications of the present invention are used fordiagnosing pre-malignant or malignant tumors which may require urgenttreatment, in contrast to a benign tumor which typically does notrequire urgent (or any) medical intervention. FTIR spectroscopy (andmicrospectroscopy) is typically a simple, reagent-free and rapid methodsuitable for use as a screening test for large populations. Earlydetection of cancer generally enables early intervention and treatment,contributing to a reduced mortality rate.

For some applications, the data obtained from both the PBMC samples andthe blood plasma samples is further analyzed by suitable methods knownin the art, e.g., Artificial Neural Network and/or Cluster Analysis,and/or Principal Component Analysis, and/or Linear Discriminant Analysis(LDA) and/or Non Linear Discriminant Analysis and/or other appropriateclassification models. Typically, combining analysis of the PBMC andplasma data provides analysis results which present high sensitivity andspecificity of about 71% and 95%, respectively.

There is therefore provided in accordance with some applications of thepresent invention a method including:

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample of a subject by analyzing the sample by infraredspectroscopy; and

based on the infrared spectrum, generating an output indicative of thepresence of a benign tumor of the subject.

For some applications, the method further includes obtaining an infrared(IR) spectrum of a plasma sample of the subject by analyzing the plasmasample by infrared spectroscopy, generating the output includesgenerating the output indicative of the presence of the benign tumor ofthe subject in response to the infrared spectroscopic analyzing of thePBMC sample and the plasma sample.

For some applications, generating the output includes indicating via theoutput that the tumor is not a malignant tumor.

For some applications, generating the output includes indicating via theoutput that the tumor is not a pre-malignant condition.

For some applications, generating the output includes indicating via theoutput that the tumor is not a pre-malignant condition and is not amalignant tumor.

For some applications, generating the output includes indicating thatthe output is differentially indicative of the presence of the benigntumor rather than the absence of a tumor.

For some applications, the benign tumor includes a benign tumor intissue selected from the group consisting of: breast tissue andgastrointestinal tract tissue, and generating the output includesgenerating an output indicative of the presence of a benign tumor in theselected tissue.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 837.4±4 cm-1, 1027.9±4 cm-1, 1182.6±4 cm-1, 1213.0±4 cm-1, 1278.1±4cm-1, 1544.2±4 cm-1, 1011.0±4 cm-1, 1071.7, 1141.7±4 cm-1, 1158.0±4cm-1, 1181.7±4 cm-1, and 1502.3±4 cm-1, the selected tissue includes thebreast tissue, and generating includes generating an output indicativeof the presence of a benign tumor in the breast tissue.

For some applications, analyzing includes assessing the characteristicat at least two wavenumbers selected from the group.

For some applications, analyzing includes assessing the characteristicat at least three wavenumbers selected from the group.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 837.4±4 cm-1, 1027.9±4 cm-1, 1182.6±4 cm-1, 1213.0±4 cm-1, 1278.1±4cm-1, and 1544.2±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than the absence of a tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 1011.0±4 cm-1, 1071.7, 1141.7±4 cm-1, 1158.0±4 cm-1, 1181.7±4 cm-1,and 1502.3±4 cm-1, and generating the output includes indicating thatthe output is differentially indicative of the presence of the benigntumor rather than a malignant tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 785.4±4 cm-1, 811.9±4 cm-1, 879.9±4 cm-1, 1253.0±4 cm-1, 1485.4±4cm-1, and 1526.9±4 cm-1, 760.8±4 cm-1, 870.7±4 cm-1, 1371.1±4 cm-1,1485.9±4 cm-1, 1526.9±4 cm-1, and 1627.1±4 cm-1, the selected tissueincludes the gastrointestinal tract tissue, and generating includesgenerating an output indicative of the presence of a benign tumor in thegastrointestinal tract tissue.

For some applications, analyzing includes assessing the characteristicat at least two wavenumbers selected from the group.

For some applications, analyzing includes assessing the characteristicat at least three wavenumbers selected from the group.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 785.4±4 cm-1, 811.9±4 cm-1, 879.9±4 cm-1, 1253.0±4 cm-1, 1485.4±4cm-1, and 1526.9±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than the absence of a tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 760.8±4 cm-1, 870.7±4 cm-1, 1371.1±4 cm-1, 1485.9±4 cm-1, 1526.9±4cm-1, and 1627.1±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than a malignant tumor.

For some applications, analyzing the sample includes obtaining a secondderivative of the infrared (IR) spectrum of the sample.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a plasma blood sample of asubject by analyzing the sample by infrared spectroscopy; and

based on the infrared spectrum, generating an output indicative of thepresence of a benign tumor of the subject.

For some applications, generating the output includes indicating via theoutput that the tumor is not a malignant tumor.

For some applications, generating the output includes indicating via theoutput that the tumor is not a pre-malignant condition.

For some applications, generating the output includes indicating via theoutput that the tumor is not a pre-malignant condition and is not amalignant tumor.

For some applications, generating the output includes indicating thatthe output is differentially indicative of the presence of the benigntumor rather than the absence of a tumor.

For some applications, the benign tumor includes a benign tumor intissue selected from the group consisting of: breast tissue andgastrointestinal tract tissue, and generating the output includesgenerating an output indicative of the presence of a benign tumor in theselected tissue.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 761.3±4 cm-1, 1117.5±4 cm-1, 1152.3±4 cm-1, 1310.9±4 cm-1, 1388.0±4cm-1, and 1453.6±4 cm-1, 761.7±4 cm-1, 1020.2±4 cm-1, 1249.2±4 cm-1,1560.1±4 cm-1, 1647.9±4 cm-1, and 1736.1±4 cm-1, the selected tissueincludes the breast tissue, and generating includes generating an outputindicative of the presence of a benign tumor in the breast tissue.

For some applications, analyzing includes assessing the characteristicat at least two wavenumbers selected from the group.

For some applications, analyzing includes assessing the characteristicat at least three wavenumbers selected from the group.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 761.3±4 cm-1, 1117.5±4 cm-1, 1152.3±4 cm-1, 1310.9±4 cm-1, 1388.0±4cm-1, and 1453.6±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than the absence of a tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 761.7±4 cm-1, 1020.2±4 cm-1, 1249.2±4 cm-1, 1560.1±4 cm-1, 1647.9±4cm-1, and 1736.1±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than a malignant tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 780.1±4 cm-1, 872.6±4 cm-1, 1142.1±4 cm-1, 1378.9±4 cm-1, 1399.6±4cm-1, and 1622.8±4 cm-1, 948.3±4 cm-1, 1034.6±4 cm-1, 1110.3±4 cm-1,1153.2±4 cm-1, 1340.3±4 cm-1, and 1378.4±4 cm-1, the selected tissueincludes the gastrointestinal tract tissue, and generating includesgenerating an output indicative of the presence of a benign tumor in thegastrointestinal tract tissue.

For some applications, analyzing includes assessing the characteristicat at least two wavenumbers selected from the group.

For some applications, analyzing includes assessing the characteristicat at least three wavenumbers selected from the group.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 780.1±4 cm-1, 872.6±±4 cm-1, 1142.1±4 cm-1, 1378.9±4 cm-1, 1399.6±4cm-1, and 1622.8±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than the absence of a tumor.

For some applications, analyzing includes assessing a characteristic ofthe sample at at least one wavenumber selected from the group consistingof: 948.3±4 cm-1, 1034.6±4 cm-1, 1110.3±4 cm-1, 1153.2±4 cm-1, 1340.3±4cm-1, and 1378.4±4 cm-1, and generating the output includes indicatingthat the output is differentially indicative of the presence of thebenign tumor rather than a malignant tumor.

For some applications, analyzing the sample includes obtaining a secondderivative of the infrared (IR) spectrum of the sample.

There is additionally provided in accordance with some applications amethod including:

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample by analyzing the sample by infrared spectroscopy;and

based on the infrared spectrum, generating an output indicative of thepresence of a solid tumor in gynecological tissue of a subject.

For some applications, the solid tumor in gynecological tissue includesa solid tumor in tissue selected from the group consisting of: ovariantissue, endometrial tissue, and cervical tissue, and generating theoutput includes generating an output indicative of the presence of asolid tumor in tissue selected from the group.

For some applications, the solid tumor is a sarcoma.

There is still provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a blood plasma sample byanalyzing the sample by infrared spectroscopy; and

based on the infrared spectrum, generating an output indicative of thepresence of a solid tumor in gynecological tissue of a subject.

For some applications, the solid tumor in gynecological tissue includesa solid tumor in tissue selected from the group consisting of: ovariantissue, endometrial tissue, and cervical tissue, and generating theoutput includes generating an output indicative of the presence of asolid tumor in tissue selected from the group.

For some applications, the solid tumor is a sarcoma.

There is still further provided in accordance with some applications amethod including:

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample of a subject and an infrared (IR) spectrum of aplasma sample of the subject by analyzing the sample by infraredspectroscopy; and

based on the infrared spectrum, generating an output indicative of thepresence of a solid malignant tumor of the subject,

generating the output includes generating the output indicative of thepresence of the tumor of the subject in response to the infraredspectroscopic analyzing of the PBMC sample and the plasma sample.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a population of Peripheral BloodMononuclear Cells (PBMC) from a subject exhibiting a clinical parameterthat may trigger a false positive diagnosis of a malignant condition, byanalyzing the cells by infrared spectroscopy; and

based on the infrared (IR) spectrum, generating an output that isdifferentially indicative of the presence of a malignant conditionversus the presence of a clinical parameter that may trigger a falsepositive diagnosis.

For some applications, the subject exhibiting a clinical parameter thatmay trigger a false positive diagnosis of a malignant condition includesa pregnant woman, and generating an output includes generating an outputthat is differentially indicative of the presence of a malignantcondition versus the presence of a pregnancy.

There is yet further provided in accordance with some applications amethod including:

obtaining an infrared (IR) spectrum of a blood plasma sample from asubject exhibiting a clinical parameter that may trigger a falsepositive diagnosis of a malignant condition, by analyzing the sample byinfrared spectroscopy; and

based on the infrared (IR) spectrum, generating an output that isdifferentially indicative of the presence of a malignant conditionversus the presence of a clinical parameter that may trigger a falsepositive diagnosis.

For some applications, the subject exhibiting a clinical parameter thatmay trigger a false positive diagnosis of a malignant condition includesa pregnant woman, and generating an output includes generating an outputthat is differentially indicative of the presence of a malignantcondition versus the presence of a pregnancy.

There is further provided in accordance with some applications a methodincluding

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample of a subject by analyzing the sample by infraredspectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output indicative of the presence of a benign tumor of thesubject.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a plasma blood sample of asubject by analyzing the sample by infrared spectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output indicative of the presence of a benign tumor of thesubject.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample from a subject, by analyzing the sample by infraredspectroscopy;

analyzing the infrared spectrum, using a processor; and

based on the analyzing using the processor, using an output device,generating an output indicative of the presence of a solid tumor ingynecological tissue of the subject.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a blood plasma sample of asubject by analyzing the sample by infrared spectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output indicative of the presence of a solid tumor ingynecological tissue of the subject.

There is further provided in accordance with some applications a methodincluding:

obtaining an infrared (IR) spectrum of a Peripheral Blood MononuclearCells (PBMC) sample of a subject and an infrared (IR) spectrum of aplasma sample of the subject by analyzing the sample by infraredspectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output indicative of the presence of a solid malignanttumor of the subject,

wherein generating the output comprises generating the output indicativeof the presence of the tumor of the subject in response to the infraredspectroscopic analyzing of the PBMC sample and the plasma sample.

There is further provided a method for diagnosis of a solid tumor, themethod including:

obtaining an infrared (IR) spectrum of a population of Peripheral BloodMononuclear Cells (PBMC) from a subject exhibiting a clinical parameterthat may trigger a false positive diagnosis of a malignant condition, byanalyzing the cells by infrared spectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output that is differentially indicative of the presenceof a malignant condition versus the presence of a clinical parameterthat may trigger a false positive diagnosis.

There is further provided a method for diagnosis of a solid tumor, themethod including:

obtaining an infrared (IR) spectrum of a blood plasma sample from asubject exhibiting a clinical parameter that may trigger a falsepositive diagnosis of a malignant condition, by analyzing the sample byinfrared spectroscopy;

analyzing the infrared spectrum using a processor; and

based on the analyzing using the processor, using an output device,generating an output that is differentially indicative of the presenceof a malignant condition versus the presence of a clinical parameterthat may trigger a false positive diagnosis.

There is further provided in accordance with some applications acomputer program product for administering processing of a body of data,the product including a computer-readable medium having programinstructions embodied therein, which instructions, when read by acomputer, cause the computer to:

obtain an infrared (IR) spectrum of a blood plasma sample by analyzingthe blood plasma sample by infrared spectroscopy; and

based on the infrared spectrum, generate an output indicative of thepresence of a benign tumor.

There is further provided in accordance with some applications computerprogram product for administering processing of a body of data, theproduct including a computer-readable medium having program instructionsembodied therein, which instructions, when read by a computer, cause thecomputer to:

obtain an infrared (IR) spectrum of a Peripheral Blood Mononuclear Cells(PBMC) sample by analyzing the blood sample by infrared spectroscopy;and

based on the infrared spectrum, generate an output indicative of thepresence of a benign tumor.

There is further provided in accordance with some applications systemfor diagnosing a benign tumor, including:

a processor, configured to analyze an infrared (IR) spectrum of a bloodplasma sample of a subject; and

an output device, configured to generate an output indicative of thepresence of a benign tumor, based on the infrared (IR) spectrum.

There is further provided in accordance with some applications a systemfor diagnosing a benign tumor, including:

a processor, configured to analyze an infrared (IR) spectrum of aPeripheral Blood Mononuclear Cells (PBMC) sample of a subject; and

an output device, configured to generate an output indicative of thepresence of a benign tumor, based on the infrared (IR) spectrum.

The present invention will be more fully understood from the followingdetailed description of embodiments thereof, taken together with thedrawings, in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-D are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra, and analysis thereof, based onPBMC samples from breast cancer patients, subjects with benign breasttumors, and controls, derived in accordance with some applications ofthe present invention;

FIGS. 2A-D are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra, and analysis thereof, based onplasma samples from breast cancer patients, subjects with benign breasttumors, and controls, derived in accordance with some applications ofthe present invention;

FIGS. 3A-H are graphs representing statistical analysis and clusteranalysis thereof including receiver operating characteristic (ROC) curveanalysis of the FTIR absorption spectra analysis, based on PBMC andplasma samples from breast cancer patients, subjects with benign breasttumors, and controls, derived in accordance with some applications ofthe present invention;

FIGS. 4A-D are graphs representing analysis of clinical information ofbreast cancer patients, for PBMC samples and plasma samples obtainedfrom the breast cancer patients in accordance with some applications ofthe present invention;

FIGS. 5A-D are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra, and analysis thereof, based onPBMC samples from colorectal cancer patients, subjects with benigncolorectal tumors, and controls, derived in accordance with someapplications of the present invention;

FIGS. 6A-E are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra, and analysis thereof, based onplasma samples from colorectal cancer patients, subjects with benigncolorectal tumors, and controls, derived in accordance with someapplications of the present invention;

FIGS. 7A-H are graphs representing statistical analysis includingreceiver operating characteristic (ROC) curve analysis of the FTIRabsorption spectra analysis, based on PBMC and plasma samples fromcolorectal cancer patients, subjects with benign colorectal tumors, andcontrols, derived in accordance with some applications of the presentinvention;

FIGS. 8A-D are graphs representing analysis of clinical information ofcolorectal cancer patients, for PBMC samples and plasma samples obtainedfrom the colorectal cancer patients in accordance with some applicationsof the present invention;

FIGS. 9A-D are graphs representing statistical analysis of PBMC andplasma samples from colorectal cancer patients, subjects withpre-malignant colorectal tumors, subjects with benign colorectal tumors,and controls, derived in accordance with some applications of thepresent invention;

FIGS. 10A-E are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra, and analysis thereof, based onPBMC samples from: gynecological cancer patients, subjects with benigngynecological tumors, pregnant subjects, and healthy controls, derivedin accordance with some applications of the present invention;

FIGS. 11A-E are graphs representing FTIR absorption spectra, the secondderivative of the absorption spectra and analysis thereof, based onplasma samples from: gynecological cancer patients, subjects with benigngynecological tumors, pregnant subjects and healthy controls, derived inaccordance with some applications of the present invention;

FIGS. 12A-B are graphs representing statistical analysis of FTIR spectraof PBMC and plasma samples from gynecological cancer patients,colorectal cancer patients and breast cancer patients derived inaccordance with some applications of the present invention;

FIGS. 13A-D are graphs representing the second derivative of FTIRabsorption spectra, and analysis thereof, based on PBMC and plasmasamples from cancer patients and healthy controls, derived in accordancewith some applications of the present invention;

FIGS. 14A-C are graphs representing statistical analysis includingreceiver operating characteristic (ROC) curve analysis of the FTIRspectra, based on analysis of PBMC and plasma samples from cancerpatients and healthy controls, derived in accordance with someapplications of the present invention;

FIGS. 15A-D are schematic illustrations of slides containing abiological sample that was air dried for 0.5 h under laminar flow at atemperature of 30±4 C to remove water in accordance with someapplications of the present invention, compared to slides containing abiological sample that was air dried for 0.5 h under laminar flow at atemperature of 21 C to remove water; and

FIG. 16 is a block diagram of a system for differential diagnosis ofbenign and malignant solid tumors, in accordance with some applicationsof the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Some applications of the present invention comprise apparatus andmethods for performing differential diagnosis of benign and malignantsolid tumors by FTIR microspectroscopy (MSP) techniques. In accordancewith some applications of the present invention, FTIR microspectroscopyis used to differentially diagnose a solid tumor and a benign tumorbased on biochemical properties of a blood and/or plasma sample of asubject. Some applications of the present invention comprise obtaining ablood sample from a subject and analyzing PBMC and/or plasma from thesample by FTIR-MSP techniques for the detection of a malignant or abenign solid tumor. Typically, blood plasma and/or a PBMC sample of apatient having a benign solid tumor is identified as exhibiting FTIRspectra that are different from FTIR spectra produced by bloodplasma/PBMC from a subject who has a malignant solid tumor.Additionally, blood plasma and/or a PBMC sample of a patient sufferingfrom a benign solid tumor is identified as exhibiting FTIR spectra thatare different from FTIR spectra produced by blood plasma/PBMC from asubject who does not suffer from a malignant or benign solid tumor (forsome applications the control group may include subjects suffering froma pathology that is not a solid tumor). Accordingly, some applicationsof the present invention provide a useful method for diagnosing a cancerpatient and distinguishing between a cancer patient and a subject with abenign tumor.

Methods Used in Some Embodiments of the Present Invention

A series of protocols are described hereinbelow which may be usedseparately or in combination, as appropriate, in accordance withapplications of the present invention. It is to be appreciated thatnumerical values are provided by way of illustration and not limitation.Typically, but not necessarily, each value shown is an example selectedfrom a range of values that is within 20% of the value shown. Similarly,although certain steps are described with a high level of specificity, aperson of ordinary skill in the art will appreciate that other steps maybe performed, mutatis mutandis.

In accordance with some applications of the present invention, thefollowing methods were applied:

Obtaining Patient and Control Populations

All studies were approved by the local Ethics Committee of the EdithWolfson Medical Center, Holon, Israel, and Beilinson Hospital, Israel.Studies were conducted in accordance with the Declaration of Helsinki.Qualified personnel obtained informed consent from each individualparticipating in this study.

A first patient population included subjects diagnosed with solid tumorsin breast and gastrointestinal tissue as set forth in the followingTable A:

TABLE A Gastrointestinal tissue Breast tissue (colorectal) ControlBenign Cancer Control Benign Cancer Number 15 15 29 15  14  35 ofsubjects. Mean 42 ± 14 46 ± 21 60 ± 13 55 ± 16 71 ± 10 67 ± 14 age ± SDGender Male — — — 8 7 19 Female 15 15 29 7 7 16 Disease Premal- — — 0 —— 6 stage ignant I — — 11 — — 6 II — — 13 — — 13 III — — 2 — — 8 IV — —0 — — 2

The diagnosis of cancer was determined by clinical, surgical,histological, and pathologic diagnosis. The pathologic stage of thetumor was determined according to tumor-node-metastasis (TNM)classification, as described in “TNM Classification of MalignantTumours”, by Sobin L H. et al., 7th Edition, New York: John Wiley, 2009.Clinical details for breast and colorectal cancer patient is presentedin FIG. 4A.

A control group (n=15) included healthy volunteers.

A second patient population included subjects diagnosed with solidtumors in gynecological tissue as set forth in the following Table B:

TABLE B Gastro- Control Breast intestinal Lung Other Mean age ± 52 ± 1459 ± 12 66 ± 13 59 ± 8 47 ± 15 SD Gender Male 18 0 27 9 3 Female 37 4224 2 2 Disease Pre 0 0 6 0 0 stage I 0 11 3 0 1 II 0 17 13 1 0 III 0 411 3 1 IV 0 1 8 7 0

The diagnosis of cancer was determined by clinical, surgical,histological, and pathologic diagnosis. The pathologic stage of thetumor was determined according to tumor-node-metastasis (TNM)classification, as described in “TNM Classification of MalignantTumours”, by Sobin L H. et al., 7th Edition, New York: John Wiley, 2009.

A control group (n=28) included healthy volunteers.

An additional control group consisted of pregnant women (n=11).

Collection of Blood Samples

1-2 ml of peripheral blood was collected in 5 ml EDTA blood collectiontubes (BD Vacutainer® Tubes, BD Vacutainer, Toronto) from patients andcontrols using standardized phlebotomy procedures. Samples wereprocessed within two hours of collection.

Extraction of Peripheral Blood Mononuclear Cells (PBMC)

Platelet-depleted residual leukocytes obtained from cancer patients andhealthy controls were applied to Histopaque 1077 gradients (SigmaChemical Co., St. Louis, Mo., USA) following manufacturer's protocol toobtain PBMC.

The cells were aspirated from the interface, washed twice with isotonicsaline (0.9% NaCl solution) at 500 g for 7 minutes, and resuspended in10 ul fresh isotonic saline. The cells were diluted with saline todifferent concentrations (respectively, by 1×, 2×, 3×, 5× and 6×), and0.4 ul from each concentration was deposited on zinc selenide (ZnSe)slides to form a uniform layer of dried cells. It is noted that anyother suitable slide may be used, e.g., reflection measurements may becarried out using a gold slide. The slides were then air dried for 0.5 hunder laminar flow at a temperature of 30±4 C to remove water. The driedcells were then assessed by FTIR microscopy.

Isolation of Plasma from Peripheral Blood Samples

Blood from cancer patients and healthy controls was diluted 1:1 inisotonic saline (0.9% NaCl solution). The diluted blood was appliedcarefully to Histopaque 1077 gradients (Sigma Chemical Co., St. Louis,Mo., USA) in 15 ml collection tubes, and centrifuged at 400 g for 30min.

To discard platelets and cell debris, the plasma was transferred to 1.5ml eppendorf tubes and centrifuged at 6000 g for 10 min. Then, 500 ul ofthe mid section of the plasma was transferred to a new eppendorf tube,and 0.8 ul of plasma was deposited on a zinc selenide (ZnSe) slide. Itis noted that any other suitable slide may be used, e.g., reflectionmeasurements may be carried out using a gold slide. The slide was airdried for 0.5 h under laminar flow at a temperature of 30±4 C to removewater. The dried plasma was then subjected to FTIR microscopy.

FTIR-Microspectroscopy

Fourier Transform Infrared Microspectroscopy (FTIR-MSP) and DataAcquisition Measurements were performed using the FTIR microscopeNicolet Centaurus with a liquid-nitrogen-cooledmercury-cadmium-telluride (MCT) detector, coupled to the FTIRspectrometer Nicolet iS10, using OMNIC software (Nicolet, Madison,Wis.). To achieve high signal-to-noise ratio (SNR), 128 coadded scanswere collected in each measurement in the wavenumber region 700 to 4000cm-1. The measurement site was circular, with a diameter of 100 um andspectral resolution of 4 cm-1 (0.482 cm-1 data spacing). To reduceplasma sample thickness variation and achieve proper comparison betweendifferent samples, the following procedures were adopted:

1. Each sample was measured at least five times at different spots.

2. Analog to Digital Converter (ADC) rates were empirically chosenbetween 2000 to 3000 counts/sec (providing measurement areas withsimilar material density).

3. The obtained spectra were baseline corrected using the rubber bandmethod, with 64 consecutive points, and normalized using vectornormalization in OPUS software as described in an article entitled“Early spectral changes of cellular malignant transformation usingFourier transformation infrared microspectroscopy”, by Bogomolny et al.,2007. J Biomed Opt. 12:024003.

In order to obtain precise absorption values at a given wavenumber withminimal background interference, the second derivative spectra were usedto determine concentrations of bio-molecules of interest. This method issusceptible to changes in FWHM (full width at half maximum) of the IRbands. However, in the case of biological samples, all samples (plasma)from the same type are composed of similar basic components, which giverelatively broad bands. Thus, it is possible to generally neglect thechanges in band FWHM, as described in an article entitled “Seleniumalters the lipid content and protein profile of rat heart: An FTIRmicrospectroscopy study”, by Toyran et al., Arch. Biochem. Biophys. 2007458:184-193.

Spectra Processing and Statistical Analysis

The IR spectrum reflects biochemical data of the measured sample. Todistinguish between cancer and control groups, specific sections fromthe selected interval of the spectra were selected as determined by theT-test. The differences were considered significant at P<0.05. Datareduction was implemented by Principal Component Analysis (PCA). If eachone of the wave numbers is considered as a direction, then the PCAtechnique searched for new directions in the data that have largestvariance and subsequently projected the data onto a newmulti-dimensional space. Following the PCA, Fisher's Linear DiscriminantAnalysis (FLDA) was performed to classify between the cancer and controlgroups. Leave-One-Out Cross-Validation (LOOCV), which is a common methodin FTIR spectral analysis, was used to evaluate the classifierperformance. The data were verified by additional unsupervisedanalytical methods such as cluster analysis using Ward's method andEuclidean distances to further verify the analysis (STATISTICA,StatSoft, Tulsa, Okla.).

EXPERIMENTAL DATA

The experiments described hereinbelow were performed by the inventors inaccordance with applications of the present invention and using thetechniques described hereinabove.

The experiments presented hereinbelow with reference to Examples 1-4demonstrate that in accordance with some applications of the presentinvention, analysis of PBMC samples and/or plasma samples by FTIR-MSPtechniques can be used for differential diagnosis of benign andmalignant solid tumors based on the FTIR-MSP spectral pattern atselected wavenumbers.

Example 1

In a set of experiments, differential diagnosis of benign breast tumorsand malignant breast tumors was performed based on a FTIR-MSP spectralpattern at selected wavenumbers of PBMC samples.

In accordance with applications of the present invention, PBMC samplesfrom 15 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control PBMC.Additionally, PBMC samples from 29 breast cancer patients were subjectedto FTIR-MSP analysis and compared to the control FTIR-MSP spectralpattern. Additionally, PBMC samples from 15 subjects with a benign tumorin breast tissue were subjected to FTIR-MSP analysis and compared to thecontrol FTIR-MSP spectral pattern and to the breast cancer FTIR-MSPspectral pattern. The PBMC samples were obtained by preliminaryprocessing of the peripheral blood in accordance with the protocolsdescribed hereinabove with reference to extraction of peripheral bloodmononuclear cells (PBMC). The PBMC samples were then analyzed byFTIR-MSP, in accordance with the protocols described hereinabove withreference to FTIR-MSP.

Reference is made to FIGS. 1A-D, which are graphs representing FTIRabsorption spectra and the second derivative of the absorption spectraand analysis thereof, for PBMC samples from 29 breast cancer patients,15 subjects with benign tumors in breast tissue and 15 healthy controls,derived in accordance with some applications of the present invention.

FIG. 1A shows average FTIR-MSP absorption spectra of PBMC samples ofhealthy controls, subjects with benign breast tumors and breast cancerpatients in the regions of 700-1800 cm-1, after baseline correction andvector normalization. Each spectrum represents the average of fivemeasurements at different sites for each sample. The spectra arecomposed of several absorption bands, each corresponding to specificfunctional groups of specific macromolecules such as lipids, proteins,carbohydrates and nucleic acids. Generally, the FTIR spectrum istypically analyzed by tracking changes vs. control in absorption(intensity and/or shift) of these macromolecules.

Table C represents some of the main IR absorption bands for PBMC cells,and their corresponding molecular functional groups:

TABLE C Wavenumber (cm−1 ± 4) Assignment 2958 ν_(as) CH₃, mostlyproteins, lipids 2922 ν_(as) CH₂, mostly lipids, proteins 2873 ν_(s)CH₃, mostly proteins, lipids 2854 ν_(s) CH₂, mostly lipids, proteins~1,656 Amide I ν C═O (80%), ν C—N (10%), δ N—H ~1,546 Amide II δ N—H(60%), ν C—N (40%) 1400 ν COO—, δ s CH3 lipids, proteins 1313 Amide IIIband components of proteins 1240 ν_(as) PO₂ ⁻, phosphodiester groups ofnucleic acids 1170 C—O bands from glycomaterials and proteins 1155 νC—Oof proteins and carbohydrates 1085 νs PO2— of nucleic acids,phospholipids, proteins 1053 ν C—O & δ C—O of carbohydrates 996 C—C &C—O of ribose of RNA 967 C—C & C—O of deoxyribose skeletal motions ofDNA 780 sugar-phosphate Z conformation of DNA 740 ν N═H of Thymine

Reference is made to FIG. 1B. In order to achieve effective comparisonbetween the PBMC samples of the breast cancer patients, subjects withbenign breast tumors and the controls, the second derivative of thebaseline-corrected, vector-normalized FTIR-MSP spectra was used. Resultsare presented in FIG. 1B. As shown from the second derivative spectraanalysis, the spectra of PBMC samples from the breast cancer patientsdiffered significantly from the spectra of PBMC samples from both thesubjects with benign breast tumors and the controls, in the spectralregion of 1140 cm-1.

The mean±standard error of the mean SEM for each of the data sets(healthy, benign, breast cancer) is represented by the thickness of thegraph lines representing the healthy, benign, and breast cancer groups,in accordance with the figure legend, as shown in FIG. 1B.

Reference is made to FIGS. 1C-D, which are graphs representing values ofthe second derivative of absorption spectra of PBMC samples fromsubjects with benign breast tumors compared to PBMC samples from cancerpatients and/or to PBMC samples from healthy controls (indicated ashealthy in the figures), derived in accordance with some applications ofthe present invention. Statistical analysis was performed and p-valuesare provided. As shown:

-   -   a) The second derivative of FTIR-MSP spectra of PBMC samples        from the breast cancer patients differed significantly from the        second derivative of FTIR-MSP spectra from PBMC of healthy        controls;    -   b) The second derivative of FTIR-MSP spectra of PBMC samples        from the breast cancer patients differed significantly from the        second derivative of FTIR-MSP spectra from PBMC of subjects with        a benign breast tumor; and    -   c) The second derivative of FTIR-MSP spectra of PBMC samples        from the subjects with a benign breast tumor differed        significantly from the second derivative of FTIR-MSP spectra        from PBMC of healthy controls.

Table D lists wavenumbers that were identified in this set ofexperiments as presented in FIGS. 1A-D. Typically, PBMC samples wereanalyzed by FTIR-MSP techniques using these wavenumbers to distinguishbetween: a) healthy control and breast cancer patients; b) healthycontrol and subjects with benign breast tumors; and c) breast cancerpatients and subjects with benign breast tumors. For some applications,the PBMC samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table D. Alternatively, the PBMC samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table D.

TABLE D Healthy control vs. Benign Healthy control vs. Cancer Benign vs.Cancer Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4)712.1 928.6 1537.5 711.6 1459.4 1608.3 729.0 1173.0 1542.3 725.6 945.91544.2 838.9 1465.2 1616.1 753.1 1181.7 1548.1 745.8 963.3 1612.7 946.91473.3 1618.9 758.9 1197.6 1559.2 758.9 1027.9 1632.9 1010.5 1498.41626.2 847.1 1253.5 1576.5 773.8 1077.5 1644.0 1082.4 1501.8 1635.3870.2 1341.7 1602.1 784.9 1116.1 1702.4 1100.7 1507.1 1641.1 882.81372.1 1612.7 793.6 1129.6 1712.0 1115.1 1512.4 1645.5 1003.8 1423.21627.1 798.4 1182.6 1778.5 1140.7 1524.9 1647.9 1011.0 1437.2 1637.3803.7 1196.6 1176.8 1528.3 1653.2 1023.5 1449.2 1642.1 837.4 1213.01213.0 1532.2 1658.5 1034.1 1466.1 1654.1 845.2 1238.6 1254.0 1535.51674.4 1047.2 1475.3 1659.9 862.5 1271.8 1278.6 1542.8 1684.5 1071.71498.9 1667.6 871.2 1278.1 1366.3 1548.1 1693.2 1080.9 1502.3 1678.7882.3 1292.6 1437.2 1551.9 1698.5 1128.2 1509.0 1709.6 897.7 1320.01443.0 1559.6 1701.4 1141.7 1524.9 1730.8 903.5 1332.6 1453.1 1568.81762.1 1158.0 1536.0

For some applications, one, two, three, or more of the followingwavenumbers selected from Table D are used to differentiate between theabsence of a tumor and a malignant breast tumor: 1140.7±4 cm-1, 1254.0±4cm-1, 1473.3±4 cm-1, 1551.9±4 cm-1, 1635.3±4 cm-1, and 1658.5±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table D are used to differentiate between theabsence of a tumor and a benign breast tumor: 837.4±4 cm-1, 1027.9±4cm-1, 1182.6±4 cm-1, 1213.0±4 cm-1, 1278.1±4 cm-1, 1544.2±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table D are used to differentiate between amalignant breast tumor and a benign breast tumor: 1011.0±4 cm-1, 1071.7,1141.7±4 cm-1, 1158.0_±4 cm-1, 1181.7±4 cm-1, 1502.3±4 cm-1.

Example 2

In a set of experiments, differential diagnosis of benign breast tumorsand malignant breast tumors was performed based on a FTIR-MSP spectralpattern of plasma samples at selected wavenumbers

In accordance with applications of the present invention, plasma samplesfrom 15 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control plasma.Additionally, plasma samples from 29 breast cancer patients weresubjected to FTIR-MSP analysis and compared to the control FTIR-MSPspectral pattern. Additionally, plasma samples from 15 subjects with abenign tumor in breast tissue were subjected to FTIR-MSP analysis andcompared to the control FTIR-MSP spectral pattern and to the breastcancer FTIR-MSP spectral pattern. The plasma samples were obtained bypreliminary processing of the peripheral blood in accordance with theprotocols described hereinabove with reference to isolation of plasmafrom peripheral blood samples. The blood plasma samples were thenanalyzed by FTIR-MSP, in accordance with the protocols describedhereinabove with reference to FTIR-MSP.

Reference is made to FIGS. 2A-D, which are graphs representing FTIRabsorption spectra and the second derivative of the absorption spectraand analysis thereof, for plasma samples from 29 breast cancer patients,15 subjects with benign tumors in breast tissue and 15 healthy controls,derived in accordance with some applications of the present invention.

FIG. 2A shows average FTIR-MSP absorption spectra of plasma samples ofhealthy controls, subjects with benign breast tumors and breast cancerpatients in the regions of 700-1800 cm-1, after baseline correction andvector normalization. Each spectrum represents the average of fivemeasurements at different sites for each sample. The spectra arecomposed of several absorption bands, each corresponding to specificfunctional groups of specific macromolecules such as lipids, proteins,and carbohydrates/nucleic acids. Generally, the FTIR spectrum istypically analyzed by tracking changes in absorption (intensity and/orshift) of these macromolecules.

Reference is made to FIG. 2B. In order to achieve effective comparisonbetween the plasma samples of the breast cancer patients, subjects withbenign breast tumors and the controls, the second derivative of thebaseline-corrected, vector-normalized FTIR-MSP spectra was used. Resultsare presented in FIG. 2B. As shown from the second derivative spectraanalysis, the spectra of the plasma samples from the breast cancerpatients differed significantly from the spectra of plasma samples fromboth the subjects with benign breast tumors and the controls, in thespectral region of 1659 cm-1 and 1653 cm-1.

The mean±SEM for each of the data sets (healthy, benign, breast cancer)is represented by the thickness of the graph lines representing thehealthy, benign, and breast cancer groups, in accordance with the figurelegend, as shown in FIG. 2B.

Reference is made to FIGS. 2C-D, which are graphs representing values ofthe second derivative of absorption spectra of plasma samples fromsubjects with benign breast tumors compared to plasma samples fromcancer patients and/or to plasma samples from healthy controls, derivedin accordance with some applications of the present invention.Statistical analysis was performed and p-values are provided. As shown:

-   -   a) The second derivative of plasma samples from the breast        cancer patients differed significantly from the second        derivative analysis of FTIR-MSP spectra from plasma of healthy        controls,    -   b) The second derivative of plasma samples from the breast        cancer patients differed significantly from the second        derivative analysis of FTIR-MSP spectra from plasma of subjects        with a benign breast tumor; and    -   c) The second derivative of plasma samples from the subjects        with a benign breast tumor differed significantly from the        second derivative analysis of FTIR-MSP spectra from plasma of        healthy controls.

Table E1 lists wavenumbers that were identified in this set ofexperiments as presented in FIGS. 2A-D. Typically, plasma samples wereanalyzed by FTIR-MSP techniques using these wavenumbers to distinguishbetween: a) control and breast cancer patients; b) control and subjectswith benign breast tumors; and c) breast cancer patients and subjectswith benign breast tumors. For some applications, the plasma samples areanalyzed by FTIR-MSP at at least one wavenumber selected from Table E1.Alternatively, the plasma samples are analyzed by FTIR-MSP at at leasttwo or three wavenumbers selected from Table E1.

TABLE E1 Healthy control vs. Benign Healthy control vs. Cancer Benignvs. Cancer Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4) Wavenumber (cm−1± 4) 724.1 1286.3 723.7 1153.2 1528.3 713.5 1512.4 1674.9 761.3 1300.3728.0 1180.7 1532.2 726.5 1525.4 1698.5 768.5 1310.9 746.8 1200.5 1534.6740.5 1528.8 1736.1 897.7 1325.3 752.6 1232.8 1542.3 756.0 1532.2 1748.6924.7 1343.7 769.9 1250.6 1547.1 761.7 1535.1 1754.4 943.5 1349.0 840.81279.1 1551.9 772.8 1542.3 1758.8 959.9 1388.0 883.2 1288.2 1559.6 867.81547.1 1765.5 980.6 1396.2 916.5 1305.1 1584.2 1020.2 1552.9 1770.8989.3 1402.5 925.7 1312.8 1612.2 1200.5 1560.1 1776.1 1013.4 1411.2943.0 1326.8 1619.4 1249.2 1565.9 1780.5 1032.7 1425.6 958.9 1342.21626.7 1267.0 1569.8 1785.8 1049.1 1453.6 965.2 1350.9 1635.8 1330.61612.2 1790.6 1054.9 1466.6 980.6 1386.6 1637.3 1355.2 1616.1 1089.61581.3 990.7 1406.8 1645.9 1378.9 1619.4 1117.5 1587.1 1021.6 1424.21652.7 1427.1 1626.7 1134.4 1731.3 1033.7 1429.5 1659.9 1437.7 1634.91146.0 1741.9 1081.4 1453.6 1667.6 1443.9 1641.1 1152.3 1752.0 1088.61480.1 1673.9 1467.6 1645.9 1169.6 1757.3 1094.9 1498.4 1699.0 1474.31647.9 1255.4 1768.9 1101.6 1502.3 1741.9 1479.6 1653.2 1266.5 1779.51118.0 1512.4 1756.8 1494.6 1659.4 1279.1 1146.5 1524.9 1767.9 1502.31667.6

For some applications, one, two, three, or more of the followingwavenumbers selected from Table E1 are used to differentiate between theabsence of a tumor and a benign breast tumor: 761.3±4 cm-1, 1117.5±4cm-1, 1152.3±4 cm-1, 1310.9±4 cm-1, 1388.0±4 cm-1, and 1453.6±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table E1 are used to differentiate between theabsence of a tumor and a malignant breast tumor: 925.7±4 cm-1, 1153.2±4cm-1, 1200.5±4 cm-1, 1350.9±4 cm-1, 1453.6±4 cm-1, 1637.3±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table E1 are used to differentiate between amalignant breast tumor and a benign breast tumor: 761.7±4 cm-1, 1020.2±4cm-1, 1249.2±4 cm-1, 1560.1±4 cm-1, 1647.9±4 cm-1, 1736.1±4 cm-1.

Reference is now made to FIGS. 1A-D, FIGS. 2A-D and FIGS. 3A-G. FIGS.3A-G are graphs representing statistical analysis including receiveroperating characteristic (ROC) curve analysis of the FTIR absorptionspectra, based on PBMC and plasma samples from breast cancer patients,subjects with benign breast tumors, and controls, as shown in FIGS. 1A-Dand FIGS. 2A-D.

FIGS. 3A-C show receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of PBMC (FIG. 3A) and plasma(FIG. 3B) of healthy controls compared to the subjects with benignbreast tumors. As shown, combined use of both the plasma and PBMCsamples (FIG. 3C) increased sensitivity and specificity for thediagnosis of a benign breast tumor.

FIGS. 3D-F show receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of PBMC (FIG. 3D) and plasma(FIG. 3E) of breast cancer patients compared to the subjects with benignbreast tumors. As shown, combined use of both the plasma and PBMCsamples (FIG. 3F) increased sensitivity and specificity fordistinguishing between a benign breast tumor and a malignant breasttumor.

FIG. 3G shows receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of combined use of both theplasma and PBMC samples of breast cancer patients, compared to thesubjects with benign breast tumors and healthy controls. Values forsensitivity and specificity are presented in FIG. 3G.

FIG. 3H represents cluster analysis according to Ward's method of breastcancer patients, the subjects with benign breast tumors, and the healthycontrols, in accordance with some applications of the present invention.The second derivative data analysis shown in FIGS. 2B-D was used asinput for the cluster analysis. FIG. 3H shows a distinction between (a)cancer patients and (b) subjects with benign breast tumors and healthycontrols (the benign group and healthy controls showing closersimilarity).

Table E2 represents the data corresponding to the numbers in FIG. 3H.

TABLE E2 1 CANCER23 2 CANCER22 3 CANCER21 4 CANCER13 5 BEN6 6 CANCER17 7CANCER14 8 CANCER24 9 H6 10 CANCER11 11 CANCER20 12 H5 13 CANCER27 14CANCER19 15 CANCER25 16 CANCER18 17 CANCER15 18 CANCER6 19 BEN7 20 BEN521 CANCER9 22 CANCER16 23 CANCER5 24 CANCER7 25 CANCER1 26 CANCER3 27 H728 CANCER12 29 CANCER10 30 HGDISP 31 H4 32 H14 33 BEN8 34 H13 35 BEN1236 BEN14 37 H12 38 H10 39 H9 40 CANCER28 41 H11 42 H8 43 BEN13 44 BEN1145 BEN1 46 CANCER2 47 BEN9 48 BEN3 49 BEN15 50 BEN2 51 BEN10 52 CANCER853 H3 54 CANCER26 55 BEN4 56 H2 57 CANCER4 58 H1

Reference is now made to FIGS. 4A-D and Table E3 which include clinicalinformation for 23 breast cancer patients and analysis of PBMC samples(FIGS. 4A-B) and plasma samples (FIGS. 4C-D) obtained from the breastcancer patients in accordance with some applications of the presentinvention.

Table E3 is a table representing clinical data for 23 female breastcancer patients who took part in the studies described herein. In TableE3:

“Location at main organ” column: “R” represents Right breast and “L”represents Left breast

Pathology column: “M” represents Malignant and “U” representsUndetermined

Malignancy type column: “IDC” represents Infiltrating Ductal Carcinoma,and “ILC” represents Infiltrating Lobular Carcinoma.

“LN” means lymph node

“MS” means “mass size” (in mm)

“# m” means “number of masses”

TABLE E3 Location # at main # # Positive Vascular Stage Malignancy AgeOrgan MS m LN LN Margin Invasion Pathology T N M S No. S Sub type 39 L20 8 14 2 R1 Y M 1 1 0 2 a IDC 51 L 75 1 3 0 R0 No M 3 0 0 2 b ILC 62 L21 2 4 0 R0 No M 2 0 0 2 a IDC 55 R 15 1 9 2 R0 No M 1 1 0 2 a IDC 71 R8 1 3 0 R0 NA M 1 0 0 1 a IDC 77 R 25 1 2 0 R0 NA M 2 0 0 2 a ILC 68 L20 2 4 0 R0 NA M 1 0 0 1 a Mucinous Carcinoma (Colloid) 69 L 18 1 3 0 R0Y M 1 0 0 1 a IDC 62 R 10 1 6 0 R0 NA M 1 0 0 1 a IDC 42 L 25 NA 21 13R0 No M 2 3 0 3 c IDC + ILC 69 R NA 1 8 0 R0 No U Ductal CarcinomaIn-Situ (DCIS) 29 R 10 1 3 0 R0 No M 1 0 0 1 a IDC 51 L 28 1 34 6 R0 Y M2 2 0 3 a IDC 70 L 7 2 5 0 R0 NA M 1 0 0 1 a ILC + Mucinous 57 L NR NR11 0 NR NR M 2 0 0 2 a IDC 47 R 33 1 10 0 R0 Y M 2 0 0 2 a IDC 51 L 9 14 0 R0 NA M 1 0 0 1 a IDC 60 L 45 1 NA NA R0 NA M 2 0 0 2 a IDC 67 R 131 3 0 R0 No M 1 0 0 1 a IDC 71 R 10 1 9 0 R0 No M 1 0 0 1 a ILC 58 R 5 11 0 R0 NA M 1 0 0 1 a ILC 63 L 20 1 9 1 R0 NA M 1 1 0 2 a IDC 66 R 18 22 0 R0 Y M 1 0 0 1 a IDC

FIGS. 4A-B are graphs representing analysis of various clinicalparameters of the breast cancer patients as derived from Table E3.Statistical analysis was performed and P-values are provided. The effectof the following parameters on PBMC from breast cancer patients wasassessed: size of the mass, number of masses, positive lymph nodes (LN),malignancy type, vascular invasion and distinguishing between stage 1and stage 2 of the disease. As shown, in accordance with someapplications of the present invention, it is possible to identify aspecific pattern for each clinical parameter in the FTIR spectraobtained from PBMC samples.

Table F lists wavenumbers that were identified in the set of experimentsas presented in FIGS. 4A-B. Typically, PBMC samples were analyzed byFTIR-MSP techniques using these wavenumbers to identify the effect ofthe following clinical parameters on PBMC samples from the breast cancerpatients: size of the mass, number of masses, positive lymph nodes (LN),malignancy type, vascular invasion and distinguishing between stage 1and stage 2 of the disease. For some applications, the PBMC samples areanalyzed by FTIR-MSP at at least one wavenumber selected from Table F.Alternatively, the PBMC samples are analyzed by FTIR-MSP at at least twoor three wavenumbers selected from Table F:

TABLE F Num. of Size of Malignancy Vascular Positive Num. of Mass typeStage Invasion LN Masses (mm) 729.9 1353.8 717.4 712.6 717.4 734.3 746.3737.2 1393.8 794.0 810.9 761.3 752.6 753.5 750.7 1398.6 801.3 892.9777.7 769.0 803.2 774.8 1441.5 817.7 1261.2 825.9 807.5 818.2 785.41451.7 823.9 1306.1 832.1 884.7 824.9 848.0 1458.4 830.7 1317.1 885.2899.1 831.7 855.8 1484.4 920.8 1324.9 1097.3 911.7 864.0 865.4 1494.6925.7 1377.9 1136.3 929.0 881.3 870.7 1529.3 931.4 1410.2 1168.7 1001.8919.9 892.9 1548.6 940.6 1449.7 1277.1 1022.1 958.4 902.0 1597.3 996.11461.3 1286.8 1106.9 1058.7 908.3 1604.0 1033.7 1489.7 1293.0 1172.51136.3 912.2 1614.6 1064.5 1499.4 1319.6 1250.1 1231.3 928.1 1649.31122.9 1503.7 1324.9 1259.3 1246.3 957.5 1663.3 1139.7 1510.0 1360.51292.6 1281.0 963.8 1709.6 1161.9 1549.5 1368.7 1344.6 1394.8 1012.91725.5 1185.0 1648.4 1382.2 1353.3 1020.2 1729.8 1218.8 1753.0 1397.71376.9 1058.7 1745.7 1288.2 1762.6 1417.9 1392.4 1080.4 1751.5 1323.91769.4 1422.7 1409.2 1098.3 1762.6 1363.4 1780.5 1430.4 1450.2 1148.91775.2 1405.4 1785.3 1484.4 1456.0 1152.3 1780.5 1502.3 1791.1 1520.61461.8 1168.7 1785.8 1508.5 1725.5 1473.8 1192.3 1593.4 1745.7 1534.61241.9 1539.9 1247.7 1560.1 1270.4 1565.9 1307.0 1596.3 1318.6 1632.01326.3 1654.6 1337.9 1660.9 1343.2 1763.1

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to identify in PBMC samples adistinct spectral pattern caused by the malignancy type of the breasttumor: 785.4±4 cm-1, 848.0±4 cm-1, 1012.9±4 cm-1, 1080.4±4 cm-1,1148.9±4 cm-1, and 1451.7±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to distinguish between stage1 and stage 2 of malignant breast tumors: 717.4±4 cm-1, 801.3±4 cm-1,823.9±4 cm-1, 920.8±4 cm-1, and 1405.4±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to identify in PBMC samples adistinct spectral pattern caused by vascular invasion of a breast tumor:1306.1±4 cm-1, 1489.7±4 cm-1, 1503.7±4 cm-1, 1648.4±4 cm-1, 1762.6±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to identify in PBMC samples adistinct spectral pattern caused by the number of positive lymph nodesof a breast cancer patient: 717.4±4 cm-1, 825.9±4 cm-1, 1097.3±4 cm-1,1293.0±4 cm-1, 1417.9±4 cm-1, and 1520.6±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to identify in PBMC samples adistinct spectral pattern caused by the number of masses of a breastcancer patient: 752.6 cm-1, 769.0±4 cm-1, 899.1±4 cm-1, 911.7±4 cm-1,1353.3±4 cm-1, and 1450.2±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table F are used to identify in PBMC samples adistinct spectral pattern caused by the size of the mass (mm) of thebreast tumor: 746.3 cm-1, 818.2±4 cm-1, 919.9±4 cm-1, 1136.3±4 cm-1, and1394.8±4 cm-1.

FIGS. 4C-D are graphs representing analysis of various clinicalparameters of the breast cancer patients as derived from Table E3.Statistical analysis was performed and P-values are provided. As shown,in accordance with some applications of the present invention, it ispossible to identify a distinct spectral pattern in FTIR analysis ofplasma samples that is caused in response to at least one of thefollowing parameters: size of the mass, number of masses, positive lymphnodes (LN), malignancy type, vascular invasion and distinguishingbetween stage 1 and stage 2 of the disease.

Table G lists wavenumbers that were identified in this set ofexperiments as presented in FIGS. 4C-D. Typically, plasma samples wereanalyzed by FTIR-MSP techniques using these wavenumbers to identify thefollowing parameters based on plasma samples from the breast cancerpatients: size of the mass, number of masses, positive lymph nodes (LN),malignancy type, vascular invasion and distinguishing between stage 1and stage 2 of the disease. For some applications, the plasma samplesare analyzed by FTIR-MSP at at least one wavenumber selected from TableG. Alternatively, the plasma samples are analyzed by FTIR-MSP at atleast two or three wavenumbers selected from Table G:

TABLE G Num. of Size of Malignancy Vascular Positive Num. of Mass typeStage Invasion LN Masses (mm) 775.7 729.4 712.6 726.5 766.1 753.1 790.7757.9 813.3 746.3 792.1 757.9 830.2 763.7 836.5 892.4 837.0 781.5 866.8780.5 843.2 927.1 856.7 799.3 897.7 797.9 850.9 1023.5 893.4 814.3 922.8803.2 876.5 1174.9 915.1 890.5 951.2 809.0 902.0 1202.4 931.0 914.11070.8 815.7 913.6 1212.5 949.3 922.8 1116.6 825.4 932.4 991.7 946.91166.7 831.7 945.4 1021.1 1055.8 1211.6 852.9 1014.9 1043.3 1072.71266.5 883.2 1089.1 1073.7 1117.5 1317.6 889.5 1105.0 1102.1 1147.91447.3 890.0 1120.4 1116.6 1180.7 1466.6 907.8 1129.1 1156.1 1206.31561.6 954.6 1138.3 1173.0 1226.0 1569.3 961.8 1145.5 1179.7 1397.21692.7 968.6 1150.8 1206.3 1608.8 1699.5 979.2 1173.0 1235.7 1626.21712.0 985.0 1211.1 1266.5 1717.8 997.0 1237.6 1292.1 1736.6 1012.91244.8 1317.1 1740.9 1024.0 1266.5 1328.2 1761.2 1040.4 1280.5 1387.51057.8 1291.1 1414.0 1077.5 1316.2 1430.9 1095.4 1328.2 1453.1 1110.81332.6 1459.4 1134.9 1380.3 1491.7 1147.0 1412.1 1497.0 1190.8 1424.21499.9 1201.0 1430.9 1504.7 1224.1 1445.9 1527.3 1255.0 1529.8 1567.41264.6 1578.9 1579.4 1271.8 1611.2 1589.1 1282.9 1621.4 1608.3 1344.11642.6 1613.6 1355.2 1653.2 1639.2 1366.3 1678.2 1373.6 1737.1 1427.11438.6 1512.9 1546.6 1553.9 1560.6 1572.7 1609.3 1616.5 1662.3

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to identify in plasma samplesa distinct spectral pattern caused by a malignancy type of the breasttumor: 775.7±4 cm-1, 897.7±4 cm-1, 922.8±4 cm-1, 1070.8±4 cm-1, 1447.3±4cm-1, and 1569.35±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to distinguish between stage1 and stage 2 of malignant breast tumors: 763.7±4 cm-1, 809.0±4 cm-1,889.5±4 cm-1, 961.8±4 cm-1, 1255.0±4 cm-1, and 1190.8±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to identify in plasma samplesa distinct spectral pattern caused by vascular invasion of a breasttumor: 843.2±4 cm-1, 876.5±4 cm-1, 1145.5±4 cm-1, 1316.2±4 cm-1,1328.2±4 cm-1, 1412.1±4 cm-1, and 1578.91±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to identify in plasma samplesa distinct spectral pattern caused by the number of positive lymph nodesof a breast cancer patient: 746.3±4 cm-1, 892.4±4 cm-1, 927.1±4 cm-1,1023.5±4 cm-1, and 1174.9±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to identify in plasma samplesa distinct spectral pattern caused by the number of masses of a breastcancer patient: 856.7 cm-1, 1043.3±4 cm-1, 1116.6±4 cm-1, 1235.7±4 cm-1,1387.5±4 cm-1, 1504.7±4 cm-1, and 1608.3±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table G are used to identify in plasma samplesa distinct spectral pattern caused by the size of the mass (mm) of thebreast tumor: 781.5 cm-1, 922.8±4 cm-1, 946.9±4 cm-1, 1072.7±4 cm-1,1147.9±4 cm-1 and 1206.3±4 cm-1.

Example 3

In a set of experiments, differential diagnosis of benigngastrointestinal (specifically colorectal) tumors and malignant andpre-malignant gastrointestinal tumors was performed based on a FTIR-MSPspectral pattern at a range of wavenumbers of PBMC samples.

In accordance with applications of the present invention, PBMC samplesfrom 15 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control PBMC.Additionally, PBMC samples from 36 colorectal cancer patients weresubjected to FTIR-MSP analysis and compared to the control FTIR-MSPspectral pattern. Additionally, PBMC samples from 14 subjects with abenign tumor in colorectal tissue were subjected to FTIR-MSP analysisand compared to the control FTIR-MSP spectral pattern and to thecolorectal cancer FTIR-MSP spectral pattern. The PBMC samples wereobtained by preliminary processing of the peripheral blood in accordancewith the protocols described hereinabove with reference to extraction ofperipheral blood mononuclear cells (PBMC). The PBMC samples were thenanalyzed by FTIR-MSP, in accordance with the protocols describedhereinabove with reference to FTIR-MSP.

For the purpose of the gastrointestinal set of experiments, the 36colorectal cancer patients included patients with pre-malignantconditions, typically, high-grade dysplasia. As shown hereinbelow, someapplications of the present invention allow distinguishing betweenpatients with a gastrointestinal pre-malignant condition (e.g., a tumorexhibiting high dysplasia) and patients with a malignant tumor ingastrointestinal tissue.

Reference is made to FIGS. 5A-D, which are graphs representing FTIRabsorption spectra and the second derivative of the absorption spectraand analysis thereof, for PBMC samples from 36 colorectal cancerpatients, 14 subjects with benign colorectal tumors and 15 healthycontrols, derived in accordance with some applications of the presentinvention.

FIG. 5A shows average FTIR-MSP absorption spectra of PBMC samples ofhealthy controls, subjects with benign colorectal tumors andgastrointestinal cancer patients in the regions of 700-1800 cm-1, afterbaseline correction and vector normalization. Each spectrum representsthe average of five measurements at different sites for each sample. Thespectra are composed of several absorption bands, each corresponding tospecific functional groups of specific macromolecules such as lipids,proteins, and carbohydrates and nucleic acids. Generally, the FTIRspectrum is typically analyzed by tracking changes in absorption(intensity and/or shift) of these macromolecules.

Reference is made to FIG. 5B. In order to achieve effective comparisonbetween the PBMC samples of the colorectal cancer patients, subjectswith benign colorectal tumors and the controls, the second derivative ofthe baseline-corrected, vector-normalized FTIR-MSP spectra was used.Results are presented in FIG. 5B. As shown from the second derivativespectra analysis, the PBMC samples from the subjects with a benign tumordiffered significantly from the spectra of PBMC samples from both thesubjects with malignant tumors and the controls, in the spectral regionof 1485 cm-1 and 1490 cm-1.

The mean±SEM for each of the data sets (healthy, benign, colorectalcancer) is represented by the thickness of the graph lines representingthe healthy, benign, and colorectal cancer groups, in accordance withthe figure legend, as shown in FIG. 5B.

Reference is made to FIGS. 5C-D, which are graphs representing values ofthe second derivative of absorption spectra of PBMC samples fromsubjects with benign colorectal tumors compared to PBMC samples fromcancer patients and/or to PBMC samples from healthy controls, derived inaccordance with some applications of the present invention. Statisticalanalysis was performed and P-values are provided. As shown:

-   -   a) The second derivative of the FTIR-MSP spectra of PBMC samples        from the colorectal cancer patients differed significantly from        the second derivative of FTIR-MSP spectra from PBMC of healthy        controls;    -   b) The second derivative of the FTIR-MSP spectra of PBMC samples        from the colorectal cancer patients differed significantly from        the second derivative of FTIR-MSP spectra from PBMC of subjects        with a benign colorectal tumor; and    -   c) The second derivative of the FTIR-MSP spectra of PBMC samples        from the subjects with a benign colorectal tumor differed        significantly from the second derivative of FTIR-MSP spectra        from PBMC of healthy controls.

Table H lists wavenumbers that were used in this set of experiments aspresented in FIGS. 5A-D. Typically, PBMC samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)control and colorectal cancer patients; b) control and subjects withbenign colorectal tumors; and c) colorectal cancer patients and subjectswith benign colorectal tumors. For some applications, the PBMC samplesare analyzed by FTIR-MSP at at least one wavenumber selected from TableH. Alternatively, the PBMC samples are analyzed by FTIR-MSP at at leasttwo or three wavenumbers selected from Table H.

TABLE H Healthy control Healthy control vs. Benign vs. Cancer Benign vs.Cancer Wavenumber Wavenumber Wavenumber (cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4)707.3 707.3 1428.0 712.6 1175.4 1509.5 1680.7 785.4 724.1 1460.8 724.11265.1 1526.9 1699.0 811.9 741.0 1475.3 760.8 1365.8 1543.7 1751.5 879.9811.9 1526.9 785.9 1371.1 1569.3 1795.9 1253.0 1033.7 1565.0 831.71378.4 1608.8 1485.4 1060.2 1613.6 870.7 1430.9 1619.9 1509.0 1141.71627.6 920.8 1460.3 1627.1 1526.9 1253.0 1638.7 999.9 1485.9 1638.71662.8 1285.3 1695.6 1020.2 1491.2 1649.8 1378.4 1796.8 1104.0 1499.91662.8

For some applications, one, two, three, or more of the followingwavenumbers selected from Table H are used to differentiate between theabsence of a tumor and a benign colorectal tumor: 785.4±4 cm-1, 811.9±4cm-1, 879.9±4 cm-1, 1253.0±4 cm-1, 1485.4±4 cm-1, and 1526.9±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table H are used to differentiate between theabsence of a tumor and a malignant colorectal tumor: 724.1±4 cm-1,741.0±4 cm-1, 1141.7±4 cm-1, 1475.3±4 cm-1, 1627.6±4 cm-1, 1695.6±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table H are used to differentiate between amalignant colorectal tumor and a benign colorectal tumor: 760.8±4 cm-1,870.7±4 cm-1, 1371.1±4 cm-1, 1485.9±4 cm-1, 1526.9±4 cm-1, 1627.1±4cm-1.

Example 4

In a set of experiments, differential diagnosis of benigngastrointestinal (specifically colorectal) tumors and malignant andpre-malignant gastrointestinal tumors was performed based on a FTIR-MSPspectral pattern at selected wavenumbers of plasma samples.

In accordance with applications of the present invention, plasma samplesfrom 15 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control plasma.Additionally, plasma samples from 36 colorectal cancer patients weresubjected to FTIR-MSP analysis and compared to the control FTIR-MSPspectral pattern. Additionally, plasma samples from 14 subjects with abenign tumor in colorectal tissue were subjected to FTIR-MSP analysisand compared to the control FTIR-MSP spectral pattern and to thecolorectal cancer FTIR-MSP spectral pattern. The plasma samples wereobtained by preliminary processing of the peripheral blood in accordancewith the protocols described hereinabove with reference to isolation ofplasma from peripheral blood samples. The plasma samples were thenanalyzed by FTIR-MSP, in accordance with the protocols describedhereinabove with reference to FTIR-MSP.

Reference is made to FIGS. 6A-E, which are graphs representing FTIRabsorption spectra and the second derivative of the absorption spectraand analysis thereof, for plasma samples from 36 colorectal cancerpatients, 14 subjects with benign colorectal tumors and 15 healthycontrols, derived in accordance with some applications of the presentinvention.

FIG. 6A shows average FTIR-MSP absorption spectra of plasma samples ofhealthy controls, subjects with benign colorectal tumors and colorectalcancer patients in the regions of 700-1800 cm-1, after baselinecorrection and vector normalization. Each spectrum represents theaverage of five measurements at different sites for each sample. Thespectra are composed of several absorption bands, each corresponding tospecific functional groups of specific macromolecules such as lipids,proteins, and carbohydrates and nucleic acids. Generally, the FTIRspectrum is typically analyzed by tracking changes in absorption(intensity and/or shift) of these macromolecules.

Reference is made to FIGS. 6B-C. In order to achieve effectivecomparison between the plasma samples of the colorectal cancer patients,subjects with benign colorectal tumors and the controls, the secondderivative of the baseline-corrected, vector-normalized FTIR-MSP spectrawas used. Results are presented in FIGS. 6B-C. As shown from the secondderivative spectra analysis, the plasma samples from the colorectalcancer patients differed significantly from the spectra of plasmasamples from both the subjects with benign colorectal tumors and thecontrols, in the spectral region of 1152 cm-1, 1172 cm-1, and 1035 cm-1.

The mean±SEM for each of the data sets (healthy, benign, colorectalcancer) is represented by the thickness of the graph lines representingthe healthy, benign, and colorectal cancer groups, in accordance withthe figure legend, as shown in FIG. 6B.

Reference is made to FIGS. 6D-E, which are graphs representing values ofthe second derivative of absorption spectra of plasma samples fromsubjects with benign colorectal tumors compared to plasma samples fromcolorectal cancer patients and/or to plasma samples from healthycontrols, derived in accordance with some applications of the presentinvention.

Statistical analysis was performed and P-values are provided. As shown:

-   -   a) The second derivative of FTIR-MSP spectra of plasma samples        from the gastrointestinal cancer patients differed significantly        from the second derivative of FTIR-MSP spectra from plasma of        healthy controls;    -   b) The second derivative of FTIR-MSP spectra of plasma samples        from the colorectal cancer patients differed significantly from        the second derivative of FTIR-MSP spectra from plasma of        subjects with a benign colorectal tumor; and    -   c) The second derivative of FTIR-MSP spectra of plasma samples        from the subjects with a benign colorectal tumor differed        significantly from the second derivative of FTIR-MSP spectra        from plasma of healthy controls.

Table I lists wavenumbers that were used in this set of experiments aspresented in FIGS. 6A-E. Typically, plasma samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)control and colorectal cancer patients; b) control and subjects withbenign colorectal tumors, and c) colorectal cancer patients and subjectswith benign colorectal tumors. For some applications, the PBMC samplesare analyzed by FTIR-MSP at at least one wavenumber selected from TableI. Alternatively, the plasma samples are analyzed by FTIR-MSP at atleast two or three wavenumbers selected from Table I.

TABLE I Healthy control Healthy control Benign vs. vs. Benign vs. CancerCancer Wavenumber Wavenumber Wavenumber (cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4)780.1 713.5 1074.6 1342.2 713.1 1053.4 1404.9 841.3 720.8 1088.6 1352.8718.8 1075.6 1420.8 872.6 780.1 1104.5 1378.9 735.2 1080.9 1430.0 1043.8816.2 1109.8 1399.1 774.3 1089.1 1460.8 1061.1 822.0 1126.2 1419.8 790.21104.0 1480.1 1142.1 829.2 1135.9 1430.4 817.2 1110.3 1510.5 1378.9840.8 1144.5 1447.3 830.2 1127.2 1612.7 1383.2 846.6 1154.7 1464.2 839.81133.9 1627.1 1399.6 859.1 1175.4 1481.1 846.1 1153.2 1662.3 1622.8904.5 1199.0 1584.2 872.1 1174.0 1729.8 922.8 1228.0 1609.3 877.5 1187.51744.3 947.4 1278.6 1613.2 904.9 1200.0 1757.8 1007.6 1289.2 1620.4921.8 1277.1 1768.9 1035.6 1313.3 1626.7 948.3 1321.0 1775.6 1052.01322.9 1662.3 964.2 1332.1 1780.9 1061.6 1331.1 1697.1 992.7 1340.31789.6 1034.6 1355.2 1049.1 1378.4

For some applications, one, two, three, or more of the followingwavenumbers selected from Table I are used to differentiate between theabsence of a tumor and a benign colorectal tumor: 780.1±4 cm-1, 872.6±4cm-1, 1142.1±4 cm-1, 1378.9±4 cm-1, 1399.6±4 cm-1, and 1622.8±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table I are used to differentiate between theabsence of a tumor and a malignant colorectal tumor: 840.8±4 cm-1,922.8±4 cm-1, 1035.6±4 cm-1, 1154.7±4 cm-1, 1352.8±4 cm-1, 1378.9±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table I are used to differentiate between amalignant colorectal tumor and a benign colorectal tumor: 948.3±4 cm-1,1034.6±4 cm-1, 1110.3±4 cm-1, 1153.2±4 cm-1, 1340.3±4 cm-1, 1378.4±4cm-1.

Reference is now made to FIGS. 5A-D, FIGS. 6A-E and FIGS. 7A-F. FIGS.7A-F are graphs representing statistical analysis including receiveroperating characteristic (ROC) curve analysis of the FTIR absorptionspectra, based on PBMC and plasma samples from colorectal cancerpatients, subjects with benign colorectal tumors, and controls, as shownin FIGS. 5A-D, and FIGS. 6A-E.

FIGS. 7A-C show receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of PBMC (FIG. 7A) and plasma(FIG. 7B) of colorectal cancer patients compared to the subjects withbenign colorectal tumor. As shown, combined use of both the plasma andPBMC samples (FIG. 7C) increased sensitivity and specificity for thedistinguishing between a benign colorectal tumor and a malignantcolorectal tumor.

FIGS. 7D-F show receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of PBMC (FIG. 7D) and plasma(FIG. 7E) of healthy controls compared to subjects with a benigncolorectal tumor. As shown, combined use of both the plasma and PBMCsamples (FIG. 7F) increased sensitivity and specificity for thediagnosis of a benign colorectal tumor.

FIG. 7G shows receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of plasma samples ofcolorectal cancer patients compared to the subjects with benign breasttumors and healthy controls. Values for sensitivity and specificity arepresented in FIG. 7G.

FIG. 7H shows receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of combined use of plasma andPBMC samples of colorectal cancer patients compared to the subjects withbenign breast tumors and healthy controls. Values for sensitivity andspecificity are presented in FIG. 7H.

Reference is now made to FIGS. 8A-D and Table J1. Table J1 includesclinical information for 23 colorectal cancer patients. FIGS. 8A-D showanalysis of PBMC samples (FIGS. 8A-B) and plasma samples (FIGS. 8C-D)obtained from the colorectal cancer patients in accordance with someapplications of the present invention.

Table J1 is a table representing clinical data for 23 colorectal cancerpatients who took part in the studies described herein. In Tale J1:

Gender column: “M” represents Male and “F” represents Female

Main organ column: “R” represents Rectum and “C” represents Colon

Location at main organ column: “Re” represents Rectum, “Rt” representsRight, “L” represents Left, “C” represents Colon, “A” representsAscending,

Pathology column: “M” represents Malignant and “PM” representsPre-Malignant

Malignancy type column: AC represents Adenocarcinoma.

“# M” represents number of masses

“MS” represents mass size (in mm)

“LN” represents number of lymph nodes

TABLE J1 Location # Main at main # Positive Vascular Stage MalignancyGender Age Organ Organ MS M LN LN Margin Invasion Pathology T N M S No SSub type M 80 R Re NA NA 10 2 R0 NA M 3 1 0 3 b AC M 66 R Re 15 1 18 0R0 No PM sessile villous adenoma HGD M 72 C A 90 1 11 0 R0 NA M 3 0 0 2a Mucinous AC M 61 C Rt 18 1 16 0 R0 No PM TVA HGD M 56 C Rt 70 1 16 12R0 NA M 3 2 0 3 c AC F 74 C L NA 1 20 0 R0 NA M 3 0 0 2 a AC F 37 C C NA1 NA NA R0 No M 1 0 0 1 — AC F 83 C L 55 1 15 0 R0 No M 3 0 0 2 a AC F82 C Rt NA 1 20 0 R0 NA M 3 0 0 2 a Mucinous AC M 69 C Rt  6 1 14 0 R0No M 3 0 0 2 a AC M 59 C Rt  9 1 10 1 R0 Yes M 3 1 0 3 b Mucinous AC M88 C Rt 33 1 18 0 R0 No M 3 0 0 2 a AC M 72 C Rt NA 1 20 0 R0 No U TVAHGD F 69 C L NA 1 4 0 R0 No M 2 0 0 1 — AC F 68 C Rt NA 1 11 4 R1 Yes M3 2 0 3 b AC F 88 C L 46 1 27 0 R0 NA M 3 0 0 2 a AC F 54 C Rt NA 1 19 0R0 No M 3 0 0 2 a AC F 84 C Rt 60 1 15 0 R0 Yes M 3 0 0 2 a AC M 81 C Rt22 1 23 0 R0 NA M 3 0 0 2 a AC F 69 C L 25 1 4 0 R0 No M 2 0 0 1 — AC M45 R Re 50 1 11 3 R0 No M 3 1 0 3 b AC M 93 C C NA NA 4 0 NA NA U TVAHGD F 78 C L NA 1 16 13 R0 Yes M 3 2 0 3 c AC

FIGS. 8A-B are graphs representing analysis of the effect of variousclinical parameters (Table J1) of the colorectal cancer patients on FTIRspectra of PBMC samples. Statistical analysis was performed and P-valuesare provided. As shown, in accordance with some applications of thepresent invention, it is possible to identify a distinct spectralpattern in FTIR analysis of PBMC samples. The distinct spectral patternis caused in response to at least one of the following parameters of thecolorectal cancer patients: size of the mass, number of masses, positivelymph nodes (LN), malignancy type, and distinguishing between stages 1and 2 and stage 3 of the disease.

Table J2 lists wavenumbers that were identified in this set ofexperiments as presented in FIGS. 8B-C. Typically, PBMC samples wereanalyzed by FTIR-MSP techniques using these wavenumbers to identifyspectral patterns for the following parameters based on PBMC samplesfrom the colorectal cancer patients: size of the mass, number of masses,positive lymph nodes (LN), malignancy type, and distinguishing betweenstages 1 and 2 and stage 3 of the disease. For some applications, thePBMC samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table J2. Alternatively, the PBMC samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table J:

TABLE J2 Malignancy Number of Num. of Size of Type Stage masses PositiveLN Mass (mm) Wavenumber Wavenumber Wavenumber Wavenumber Wavenumber(cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4) 746.3 705.3 713.5704.9 756.4 753.1 716.9 734.3 716.4 1019.2 809.5 767.0 759.8 755.01201.0 815.3 789.7 766.1 766.6 1516.3 829.2 804.7 769.9 770.9 1632.9856.7 810.0 836.5 789.7 1645.0 868.8 815.7 860.1 796.0 880.8 837.9 893.8837.9 892.9 846.6 909.3 846.6 957.5 861.1 932.9 847.1 1033.2 895.8 946.9861.1 1049.1 992.2 981.6 895.3 1061.1 1007.6 992.2 945.9 1104.0 1076.61006.2 991.2 1118.5 1266.5 1031.2 1007.1 1129.6 1274.7 1039.4 1076.61145.0 1298.3 1050.1 1183.6 1186.5 1329.2 1063.5 1232.3 1201.9 1351.91075.6 1266.5 1229.4 1371.1 1163.3 1292.6 1235.7 1446.4 1183.1 1329.71251.6 1497.9 1213.0 1351.9 1293.0 1507.6 1224.1 1371.1 1364.9 1574.61267.5 1438.2 1418.4 1605.4 1274.7 1445.9 1626.7 1657.5 1298.8 1488.31665.7 1715.9 1310.4 1550.0 1690.3 1727.9 1329.2 1575.1 1739.0 1370.71605.9 1761.2 1371.1 1657.5 1773.7 1425.6 1707.2 1535.5 1707.7 1540.41717.3 1546.1 1727.9 1558.7 1738.0 1590.5 1742.9 1673.9 1773.7 1718.31727.9 1740.4

For some applications, one, two, three, or more of the followingwavenumbers selected from Table J2 are used to identify in PBMC samplesa distinct spectral pattern caused by a malignancy type of thecolorectal tumor: 868.8±4 cm-1, 957.5±4 cm-1, 1145.0±4 cm-1, 1251.6±4cm-1, and 1364.9±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table J2 are used to distinguish between stage1 and 2 and stage 3 of colorectal tumor: 815.7±4 cm-1, 837.9±4 cm-1,895.8±4 cm-1, 992.2±4 cm-1, 1371.1±4 cm-1, 1574.6±4 cm-1 and 1657.5±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table J2 are used to identify in PBMC samplesa distinct spectral pattern caused by the number of masses of acolorectal tumor: 734.3±4 cm-1, 759.8±4 cm-1, 893.8±4 cm-1, 932.9±4cm-1, 1370.7±4 cm-1, 1412.1±4 cm-1, and 1578.9±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table J2 are used to identify in PBMC samplesa distinct spectral pattern caused by the number of positive lymph nodesof a colorectal cancer patient: 837.9±4 cm-1, 895.3±4 cm-1, 1292.6±4cm-1, 1371.1±4 cm-1, 1550.0±4 cm-1, and 1575.1±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table J2 are used to identify in PBMC samplesa distinct spectral pattern caused by the size of the mass (mm) of thecolorectal tumor: 756.4 cm-1, 1019.2±4 cm-1, 1201.0±4 cm-1, and 1516.3±4cm-1.

FIGS. 8C-D are graphs representing analysis of various clinicalparameters of the colorectal cancer patients as derived from Table J1.Statistical analysis was performed and P-values are provided. As shown,in accordance with some applications of the present invention, it ispossible to identify a distinct FTIR spectral pattern in plasma samplesdue to the following parameters of colorectal cancer patients: size ofthe mass, positive lymph nodes (LN), vascular invasion, anddistinguishing between stages 1 and 2 and stage 3 of the disease.

Table K lists wavenumbers that were identified in this set ofexperiments as presented in FIGS. 8C-D. Typically, plasma samples wereanalyzed by FTIR-MSP techniques using these wavenumbers to identify theeffect of the following parameters on FTIR spectral pattern of plasmasamples of the colorectal cancer patients: size of the mass, positivelymph nodes (LN), vascular invasion and distinguishing between stages 1and 2 and stage 3 of the disease. For some applications, the plasmasamples are analyzed by FTIR-MSP at at least one wavenumber selectedfrom Table K. Alternatively, the plasma samples are analyzed by FTIR-MSPat at least two or three wavenumbers selected from Table K:

TABLE K Vascular Num. of Size of Invasion Stage Positive LN Mass (mm)Wavenumber Wavenumber Wavenumber Wavenumber (cm−1 ± 4) (cm−1 ± 4) (cm−1± 4) (cm−1 ± 4) 729.4 1157.1 709.7 710.2 740.5 746.3 1168.2 756.4 756.4832.1 751.1 1177.3 806.6 807.1 844.7 775.7 1192.3 813.3 813.3 992.7793.1 1216.9 819.1 818.6 1051.0 808.0 1222.2 826.3 826.8 1155.2 814.81229.9 861.1 833.6 1377.4 833.6 1251.1 872.6 861.1 1426.1 857.7 1264.6945.9 872.1 1578.0 870.7 1269.9 952.2 910.2 1669.6 905.4 1282.4 971.9945.9 1712.5 912.6 1356.7 988.3 952.2 1718.3 946.4 1531.7 1018.7 1013.41728.9 958.0 1546.1 1043.8 1019.2 1740.4 976.3 1559.2 1165.3 1043.81751.0 998.0 1568.8 1196.1 1052.9 1756.8 1007.6 1572.2 1216.9 1164.81767.9 1019.2 1621.4 1245.8 1172.5 1773.2 1028.4 1635.3 1267.5 1195.61778.0 1040.4 1643.1 1279.1 1356.7 1046.2 1663.8 1288.7 1664.3 1052.91692.7 1664.3 1725.5 1074.6 1738.0 1738.0 1746.2 1143.6 1763.6

For some applications, one, two, three, or more of the followingwavenumbers selected from Table K are used to identify in plasma samplesa distinct spectral pattern caused by vascular invasion of a colorectaltumor: 976.3±4 cm-1, 1052.9±4 cm-1, 1143.6±4 cm-1, 1177.3±4 cm-1,1229.9±4 cm-, and 1356.7±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table K are used to distinguish between stage1 and 2 and stage 3 of colorectal tumor: 756.4±4 cm-1, 806.6±4 cm-1,945.9±4 cm-1, 1165.3±4 cm-1, 1196.1±4 cm-1, 1288.7±4 cm-1 and 1657.5±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table K are used to identify in plasma samplesa distinct spectral pattern caused by the number of positive lymph nodesof a colorectal cancer patient: 756.4±4 cm-1, 807.1±4 cm-1, 861.1±4cm-1, 872.1±4 cm-1, 945.9±4 cm-1, and 1164.8±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table K are used to identify in plasma samplesa distinct spectral pattern caused by the size of the mass (mm) of thecolorectal tumor: 740.5±4 cm-1, 844.7±4 cm-1, 1051.0±4 cm-1, and1377.4±4 cm-1, 1751.0±4 cm-1, 1778.0±4 cm-1.

Reference is made to FIGS. 9A-D which are graphs representingstatistical analysis and P-values of PBMC (FIGS. 9A-B) and plasmasamples (FIGS. 9C-D) from colorectal cancer patients (Cn), subjects withpre-malignant colorectal tumors (HGD), subjects with benign colorectaltumors (Bn), and healthy controls (HI), derived in accordance with someapplications of the present invention.

As shown in FIGS. 9A-B, PBMC samples that were analyzed by FTIR-MSPtechniques allow distinguishing between: a) healthy control andcolorectal cancer patients; b) healthy controls and subjects with benigncolorectal tumors vs. colorectal cancer patients; c) subjects withpre-malignant colorectal tumors exhibiting high grade dysplasia vs.cancer patients; d) healthy controls vs. colorectal cancer patients andsubjects with pre-malignant colorectal tumors exhibiting high gradedysplasia; e) healthy control and subjects with benign colorectal tumorsvs. colorectal cancer patients and subjects with pre-malignantcolorectal tumors exhibiting high grade dysplasia; and f) healthycontrols vs. subjects with benign colorectal tumors, colorectal cancerpatients and subjects with pre-malignant colorectal tumors exhibitinghigh grade dysplasia.

As shown in FIGS. 9C-D, plasma samples that were analyzed by FTIR-MSPtechniques allow distinguishing between: a) healthy control andcolorectal cancer patients; b) healthy controls and subjects with benigncolorectal tumors vs. colorectal cancer patients; c) subjects withpre-malignant colorectal tumors exhibiting high grade dysplasia vs.cancer patients; d) healthy controls vs. colorectal cancer patients andsubjects with pre-malignant colorectal tumors exhibiting high gradedysplasia; e) healthy control and subjects with benign colorectal tumorsvs. colorectal cancer patients and subjects with pre-malignantcolorectal tumors exhibiting high grade dysplasia; and f) healthycontrols vs. subjects with benign colorectal tumors, colorectal cancerpatients and subjects with pre-malignant colorectal tumors exhibitinghigh grade dysplasia.

Example 5

In a set of experiments, differential diagnosis of various types ofmalignant tumors in gynecological tissue was performed based on aFTIR-MSP spectral pattern at selected wavenumbers of PBMC samples.Additionally, differential diagnosis of malignant ovarian tumors andbenign ovarian tumors was performed based on a FTIR-MSP spectral patternat selected wavenumbers of PBMC samples. Patient data is presentedhereinabove in Table B.

As mentioned hereinabove, an additional control group for this set ofexperiments consisted of pregnant women (n=11). (Pregnancy may trigger afalse positive cancer diagnosis due to physiological changes and thepresence of blood markers. Therefore, pregnancy acts as an appropriatecontrol for gynecological tumors and for the effectiveness of someapplications of the present invention to differentiate between cancerand other non-cancerous conditions, e.g., pregnancy.)

In accordance with applications of the present invention, PBMC samplesfrom 28 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control PBMC.Additionally, PBMC samples from 11 ovarian cancer patients, 15endometrial cancer patients, 6 gynecological sarcoma patients, 7cervical cancer patients, 4 vulvar cancer patients and 3 patientsdiagnosed with a borderline ovarian tumor (BOT) were subjected toFTIR-MSP analysis and compared to the control FTIR-MSP spectral pattern.Additionally, PBMC samples from 8 subjects with a benign tumor inovarian tissue were subjected to FTIR-MSP analysis and compared to thecontrol FTIR-MSP spectral pattern and to the cancer FTIR-MSP spectralpattern. Further additionally, PBMC samples from 11 pregnant women weresubjected to FTIR-MSP analysis and compared to the control FTIR-MSPspectral pattern, to the cancer FTIR-MSP spectral pattern and to thebenign FTIR-MSP spectral pattern.

The PBMC samples were obtained by preliminary processing of theperipheral blood in accordance with the protocols described hereinabovewith reference to extraction of peripheral blood mononuclear cells(PBMC). The PBMC samples were then analyzed by FTIR-MSP, in accordancewith the protocols described hereinabove with reference to FTIR-MSP.

Results are presented in FIGS. 10A-E, which are graphs representing FTIRabsorption spectra, the second derivative of the absorption spectra, andanalysis thereof, based on PBMC samples from the gynecological cancerpatients, subjects with benign gynecological tumors, pregnant subjectsand healthy controls, derived in accordance with some applications ofthe present invention.

FIG. 10A shows average FTIR-MSP absorption spectra of PBMC samples ofhealthy controls, subjects with benign ovarian tumors and gynecologicalcancer patients in the regions of 700-1800 cm-1, after baselinecorrection and vector normalization. Each spectrum represents theaverage of five measurements at different sites for each sample. Thespectra are composed of several absorption bands, each corresponding tospecific functional groups of specific macromolecules such as lipids,proteins, and carbohydrates/nucleic acids. Generally, the FTIR spectrumis typically analyzed by tracking changes in absorption (intensityand/or shift) of these macromolecules.

Reference is made to FIGS. 10B-C. In order to achieve effectivecomparison between the PBMC samples of the various gynecological cancerpatients, subjects with benign ovarian tumors, pregnant women and thecontrols, the second derivative of the baseline-corrected,vector-normalized FTIR-MSP spectra was used. Results are presented inFIGS. 10B-C. As shown from the second derivative spectra analysis, thePBMC samples from the various cancer patients differed from the controland pregnant women group. Additionally, analysis of PBMC by FTIR-MSP ofthe various cancer patients produced distinct FTIR spectra for each typeof gynecological tumor. Accordingly, some applications of the presentinvention are used to detect a type of a gynecological solid tumor.Typically, each type of malignant gynecological solid tumor producesdistinct FTIR spectra of the PBMC, which are unique to the type of solidtumor. This can be due to each type of solid tumor inducing specificbiochemical changes in PBMC.

Reference is made to FIGS. 10D-E, which are graphs representing valuesof the second derivative of absorption spectra of PBMC samples presentedin FIGS. 10B-C. Statistical analysis was performed and P-values areprovided.

FIG. 10D shows statistical analysis and P-values for gynecologicalcancer patients compared to pregnant women and to healthy controls. Asshown,

-   -   a) The second derivative of PBMC samples from the gynecological        cancer patients differed significantly from the second        derivative analysis of FTIR-MSP spectra from PBMC of healthy        controls, and    -   b) The second derivative of PBMC samples from the pregnant women        differed significantly from the second derivative analysis of        FTIR-MSP spectra from the cancer patients.

Table L lists wavenumbers that were identified in the set of experimentsas presented in FIG. 10D. Typically, PBMC samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)control and gynecological cancer patients; and b) gynecological cancerpatients and pregnant women. For some applications, the PBMC samples areanalyzed by FTIR-MSP at at least one wavenumber selected from Table 1.Alternatively, the PBMC samples are analyzed by FTIR-MSP at at least twoor three wavenumbers selected from Table L.

TABLE L Healthy Control vs. Cancer CS (pregnant) vs. Cancer Wavenumber(cm−1 ± 4) Wavenumber (cm−1 ± 4) 706.3 1102.6 1458.4 750.2 1061.1 1538.9752.6 1117.1 1464.2 755.5 1139.2 1544.7 767.5 1134.9 1496.5 789.2 1167.71558.2 776.7 1161.4 1523.0 795.0 1178.8 1564.0 784.9 1170.1 1535.1 806.61185.0 1595.3 798.4 1186.5 1558.7 811.9 1221.7 1605.4 804.2 1201.01564.0 820.6 1240.0 1610.8 877.5 1219.3 1574.6 828.8 1261.7 1615.1 883.21228.4 1605.4 843.2 1328.7 1629.1 920.4 1237.1 1618.0 848.5 1385.61634.4 927.6 1247.7 1624.3 891.0 1403.4 1645.0 955.6 1265.6 1632.4 900.11436.2 1653.2 985.4 1274.7 1638.7 919.4 1486.8 1684.5 998.5 1305.61647.9 935.8 1497.9 1690.8 1008.6 1348.5 1653.7 994.6 1501.3 1783.41030.3 1365.4 1669.6 1000.9 1506.6 1789.1 1036.6 1370.7 1678.2 1006.21512.4 1058.2 1384.2 1684.5 1034.1 1527.3 1067.9 1389.5 1728.9 1048.61533.1 1081.9 1414.0 1783.4 1095.9 1452.1

For some applications, one, two, three, or more of the followingwavenumbers selected from Table L are used to differentiate between thehealthy controls and gynecological cancer patients: 1030.3±4 cm-1,1067.9±4 cm-1, 1134.9±4 cm-1, 1161.4±4 cm-1, 1186.5±4 cm-1, and 1389.5±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table L are used to differentiate between thepregnant women and gynecological cancer patients: 750.2±4 cm-1, 843.2±4cm-1, 1034.1±4 cm-1, 1048.6±4 cm-1, 1185.0±4 cm-1, 1506.6±4 cm-1.

FIG. 10E shows statistical analysis and p-values for ovarian cancerpatients, subjects with benign ovarian tumors and healthy controls. Asshown,

-   -   a) The second derivative of PBMC samples from the ovarian cancer        patients differed significantly from the second derivative        analysis of FTIR-MSP spectra from PBMC of healthy controls,    -   b) The second derivative of PBMC samples from healthy controls        differed significantly from the second derivative analysis of        FTIR-MSP spectra from the subjects with benign a ovarian tumor,        and    -   c) The second derivative of PBMC samples from ovarian cancer        patients differed significantly from the second derivative        analysis of FTIR-MSP spectra from the subjects with a benign        ovarian tumor.

Table M lists wavenumbers that were identified in the set of experimentsas presented in FIG. 10E. Typically, PBMC samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)healthy control and ovarian cancer patients; and b) ovarian cancerpatients and subjects with a benign ovarian tumor, and c) healthycontrol and subjects with a benign ovarian tumor. For some applications,the PBMC samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table M. Alternatively, the PBMC samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table M.

TABLE M Healthy control vs. Cancer Healthy control vs. Benign Benign vs.Cancer Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4)745.4 1096.3 1536.0 702.9 1228.0 1558.2 733.3 1408.3 752.1 1133.0 1558.2733.8 1303.6 1563.5 740.0 1445.9 776.2 1162.4 1564.0 740.5 1333.5 1575.6747.3 1523.5 783.4 1171.5 1574.1 754.0 1338.8 1582.3 753.5 1540.4 788.71188.4 1604.5 840.8 1346.1 1588.6 840.8 1551.9 797.9 1200.5 1618.0 850.51376.9 1630.0 850.5 1574.1 804.2 1219.8 1653.2 868.3 1391.9 1635.8 887.11582.8 829.2 1238.6 1666.7 880.3 1407.8 1642.1 909.8 1588.6 919.9 1330.61728.9 909.8 1440.1 1651.7 918.9 1595.8 929.5 1348.5 1740.9 1002.81445.9 1666.7 1058.7 1618.0 946.9 1354.7 1751.0 1008.6 1456.0 1678.21073.7 1629.1 956.5 1384.6 1066.4 1489.3 1685.0 1127.7 1635.8 985.41389.5 1103.6 1514.3 1694.2 1146.5 1641.1 992.2 1418.4 1121.4 1524.01747.7 1187.9 1651.7 1007.1 1468.5 1128.2 1532.2 1753.5 1237.1 1657.51029.8 1476.2 1135.4 1535.5 1771.8 1252.1 1728.4 1057.8 1497.0 1146.01540.8 1778.5 1266.5 1761.7 1068.4 1522.0 1173.5 1546.6 1794.4 1329.71773.2 1080.4 1532.6 1199.5 1552.4 1347.5 1778.5

For some applications, one, two, three, or more of the followingwavenumbers selected from Table M are used to differentiate between thehealthy controls and ovarian cancer patients: 752.1±4 cm-1, 956.5±4cm-1, 1029.8±4 cm-1, 1057.8±4 cm-1, 1162.4±4 cm-1, 1389.5±4 cm-1, and1476.2±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table M are used to differentiate between thehealthy controls and subjects with a benign ovarian tumor: 754.0±4 cm-1,1103.6±4 cm-1, 1121.4±4 cm-1, 1346.1±4 cm-1, and 1376.9±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table M are used to differentiate between thesubjects with a benign ovarian tumor and the ovarian cancer patients:753.50±4 cm-1, 850.5±4 cm-1, 918.9±4 cm-1, 1058.7±4 cm-1, 1187.9±4 cm-1and 1651.7±4 cm-1.

Example 6

In a set of experiments, differential diagnosis of various types ofmalignant tumors in gynecological tissue was performed based on aFTIR-MSP spectral pattern at selected wavenumbers of plasma samples.Additionally, differential diagnosis of malignant ovarian tumors andbenign ovarian tumors was performed based on a FTIR-MSP spectral patternat selected wavenumbers of plasma samples. Patient data is presentedhereinabove in Table B. As mentioned hereinabove, an additional controlgroup for this set of experiments consisted of pregnant women (n=11).Pregnancy may trigger a false positive cancer diagnosis due tophysiological changes, thus acting as an appropriate control forgynecological tumors.

In accordance with applications of the present invention, plasma samplesfrom 28 healthy controls were analyzed by FTIR-MSP, and a typicalFTIR-MSP spectral pattern was established for control plasma.Additionally, plasma samples from 11 ovarian cancer patients, 15endometrial cancer patients, 6 gynecological sarcoma patients, 7cervical cancer patients, 4 vulvar cancer patients and 3 patientsdiagnosed with a borderline ovarian tumor (BOT) were subjected toFTIR-MSP analysis and compared to the control FTIR-MSP spectral pattern.Additionally, plasma samples from 8 subjects with a benign tumor inovarian tissue were subjected to FTIR-MSP analysis and compared to thecontrol FTIR-MSP spectral pattern and to the cancer FTIR-MSP spectralpattern. Further additionally, plasma samples from 11 pregnant womenwere subjected to FTIR-MSP analysis and compared to the control FTIR-MSPspectral pattern, to the cancer FTIR-MSP spectral pattern and to thebenign FTIR-MSP spectral pattern.

The plasma samples were obtained by preliminary processing of theperipheral blood in accordance with the protocols described hereinabovewith reference to extraction of plasma. The plasma samples were thenanalyzed by FTIR-MSP, in accordance with the protocols describedhereinabove with reference to FTIR-MSP.

Results are presented in FIGS. 11A-E, which are graphs representing FTIRabsorption spectra, the second derivative of the absorption spectra, andanalysis thereof, based on plasma samples from the gynecological cancerpatients, subjects with benign gynecological tumors, pregnant subjectsand healthy controls, derived in accordance with some applications ofthe present invention.

FIG. 11A shows average FTIR-MSP absorption spectra of plasma samples ofhealthy controls, subjects with benign ovarian tumors and gynecologicalcancer patients in the regions of 700-1800 cm-1, after baselinecorrection and vector normalization. Each spectrum represents theaverage of five measurements at different sites for each sample. Thespectra are composed of several absorption bands, each corresponding tospecific functional groups of specific macromolecules such as lipids,proteins, and carbohydrates/nucleic acids. Generally, the FTIR spectrumis typically analyzed by tracking changes in absorption (intensityand/or shift) of these macromolecules.

Reference is made to FIGS. 11B-C. In order to achieve effectivecomparison between the plasma samples of the various gynecologicalcancer patients, subjects with benign ovarian tumors, pregnant women andthe controls, the second derivative of the baseline-corrected,vector-normalized FTIR-MSP spectra was used. Results are presented inFIGS. 11B-C. As shown from the second derivative spectra analysis, theplasma samples from the various cancer patients differed from thecontrol and pregnant women group. Additionally, analysis of plasma byFTIR-MSP of the various cancer patients produced distinct FTIR spectrafor each type of gynecological tumor. Accordingly, some applications ofthe present invention are used to detect a type of a gynecological solidtumor. Typically, each type of malignant gynecological solid tumorproduces distinct FTIR spectra of the plasma, which are unique to thetype of solid tumor. This can be due to each type of solid tumorinducing specific biochemical changes in plasma.

Reference is made to FIGS. 11D-E, which are graphs representing valuesof the second derivative of absorption spectra of plasma samplespresented in FIGS. 11B-C. Statistical analysis was performed andP-values are provided.

FIG. 11D shows statistical analysis and P-values for gynecologicalcancer patients compared to pregnant women and to healthy controls. Asshown,

-   -   a) The second derivative of plasma samples from the        gynecological cancer patients differed significantly from the        second derivative analysis of FTIR-MSP spectra from plasma of        healthy controls, and    -   b) The second derivative of plasma samples from the pregnant        women differed significantly from the second derivative analysis        of FTIR-MSP spectra from the cancer patients.

Table N lists wavenumbers that were identified in the set of experimentsas presented in FIG. 11D. Typically, plasma samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)control and gynecological cancer patients; and b) gynecological cancerpatients and pregnant women. For some applications, the plasma samplesare analyzed by FTIR-MSP at at least one wavenumber selected from TableN. Alternatively, the plasma samples are analyzed by FTIR-MSP at atleast two or three wavenumbers selected from Table N.

TABLE N Healthy Control vs. Cancer CS (pregnant) vs. Cancer Wavenumber(cm−1 ± 4) Wavenumber (cm−1 ± 4) 745.4 1100.2 1413.6 729.4 1181.2 1147.4752.6 1112.7 1421.8 740.0 1205.8 1160.0 781.5 1130.1 1435.7 749.2 1217.31168.2 821.5 1137.8 1449.2 760.8 1237.1 1523.5 830.2 1145.5 1460.3 800.81246.8 1530.2 836.5 1156.1 1475.3 846.1 1281.5 1545.7 846.6 1171.51519.2 859.1 1291.1 1557.2 856.7 1199.0 1529.3 864.9 1329.7 1564.0 870.21233.7 1544.7 926.6 1350.9 1610.3 898.2 1266.0 1564.0 938.2 1362.01621.4 906.4 1279.5 1578.5 951.2 1378.4 1634.4 919.4 1287.7 1585.2 971.01399.1 1644.5 928.6 1294.5 1620.4 992.2 1427.5 1652.7 971.5 1304.11642.1 1012.0 1436.2 1658.5 980.1 1313.8 1647.4 1019.7 1453.6 1669.1989.8 1324.9 1653.7 1030.3 1466.1 1676.8 1007.6 1336.4 1669.6 1049.61475.3 1683.1 1015.3 1349.9 1676.3 1064.5 1496.5 1689.3 1038.0 1378.91684.0 1071.7 1501.3 1714.9 1055.4 1388.0 1691.7 1079.5 1506.6 1725.51066.4 1401.5 1699.9 1091.0 1512.4 1730.8 1101.2 1519.6 1739.0 1115.11131.5 1764.1

For some applications, one, two, three, or more of the followingwavenumbers selected from Table N are used to differentiate between thehealthy controls and gynecological cancer patients: 980.1±4 cm-1,1007.6±4 cm-1, 1038.0±4 cm-1, 1055.4±4 cm-1, 1171.5±4 cm-1, and 1279.5±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table N are used to differentiate between thepregnant women and gynecological cancer patients: 740.0±4 cm-1, 971.0±4cm-1, 1019.7±4 cm-1, 1064.5±4 cm-1, 1291.1±4 cm-1, 1378.4±4 cm-1.

FIG. 11E shows statistical analysis and p-values for ovarian cancerpatients, subjects with benign ovarian tumors and healthy controls. Asshown,

-   -   a) The second derivative of the FTIR-MSP spectra of plasma        samples from the ovarian cancer patients differed significantly        from the second derivative of FTIR-MSP spectra from plasma of        healthy controls,    -   b) The second derivative of the FTIR-MSP spectra of plasma        samples from healthy controls differed significantly from the        second derivative of FTIR-MSP spectra from the subjects with        benign a ovarian tumor, and    -   c) The second derivative of the FTIR-MSP spectra of plasma        samples from ovarian cancer patients differed significantly from        the second derivative of FTIR-MSP spectra from the subjects with        a benign ovarian tumor.

Table O lists wavenumbers that were identified in the set of experimentsas presented in FIG. 11E. Typically, plasma samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)healthy control and ovarian cancer patients; and b) ovarian cancerpatients and subjects with a benign ovarian tumor, and c) healthycontrol and subjects with a benign ovarian tumor. For some applications,the plasma samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table O. Alternatively, the plasma samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table O.

TABLE O Healthy control Healthy control Benign vs. Cancer vs. Benign vs.Cancer Wavenumber Wavenumber Wavenumber (cm−1 ± 4) (cm−1 ± 4) (cm−1 ± 4)717.9 1146.5 1642.1 732.3 1432.9 705.3 1339.3 724.1 1156.6 1653.2 763.71450.7 731.9 1357.6 746.3 1172.5 1675.4 771.9 1456.0 777.2 1369.2 751.61198.1 1692.2 777.2 1461.8 787.3 1391.4 764.2 1233.3 1700.4 830.7 1488.8809.5 1456.5 786.3 1269.9 1724.5 838.4 1537.0 846.6 1490.2 792.6 1281.01761.2 849.0 1543.3 900.6 1522.5 809.0 1288.2 979.2 1557.2 967.1 1549.0818.2 1312.8 1007.6 1576.0 975.8 1618.9 832.1 1323.9 1026.9 1633.9 984.51634.4 839.8 1348.0 1045.7 1651.7 1028.4 1658.5 846.6 1379.8 1134.41666.7 1039.4 1666.7 856.7 1386.1 1153.2 1671.0 1052.5 1673.4 873.11400.1 1174.4 1676.8 1114.2 1688.4 904.0 1448.8 1218.3 1716.3 1156.11696.6 919.4 1467.1 1259.8 1722.1 1197.1 1710.6 981.1 1522.0 1276.61730.8 1218.3 1731.3 1001.4 1529.8 1290.1 1748.6 1234.2 1743.3 1007.11544.7 1320.5 1754.9 1258.8 1755.4 1036.6 1550.5 1337.4 1765.5 1274.71767.4 1056.8 1563.5 1351.4 1771.8 1293.5 1771.8 1072.2 1584.7 1391.41781.9 1318.6 1781.9 1113.7 1618.0 1398.6 1333.1 1786.2

For some applications, one, two, three, or more of the followingwavenumbers selected from Table O are used to differentiate between thehealthy controls and ovarian cancer patients: 846.6±4 cm-1, 1056.8±4cm-1, 1146.5±4 cm-1, 1156.6±4 cm-1, 1172.5±4 cm-1, 1198.1±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table O are used to differentiate between thehealthy controls and subjects with a benign ovarian tumor: 830.7±4 cm-1,1007.6±4 cm-1, 1290.1±4 cm-1, 1676.8±4 cm-1, 1716.3±4 cm-1, and 1754.9±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table O are used to differentiate between thesubjects with a benign ovarian tumor and the ovarian cancer patients:777.2±4 cm-1, 1039.4±4 cm-1, 1052.5±4 cm-1, 1156.1±4 cm-1, 1218.3±4 cm-1and 1369.2±4 cm-1.

Reference is made to Examples 1-6 and to FIGS. 12A-B. In someapplications of the present invention, analysis of PBMC and plasmasamples by FTIR-MSP is used to detect a type of solid tumor. Typically,each type of malignant solid tumor produces distinct FTIR spectra of thePBMC and plasma, which are unique to the type of solid tumor.

FIG. 12A shows statistical analysis and p-values of FTIR-MSP spectraobtained from PBMC samples of breast cancer patients, gynecologicalcancer patients and colorectal cancer patients (GI). As shown, someapplications of the present invention distinguish between

-   -   a) Breast cancer patients and colorectal cancer patients;    -   b) Breast cancer patients and gynecological cancer patients; and    -   c) Colorectal cancer patients and gynecological cancer patients.

Table P lists wavenumbers that were identified in the set of experimentsas presented in FIG. 12A. Typically, PBMC samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)breast cancer patients and colorectal cancer patients; b) breast cancerpatients and gynecological cancer patients, and c) colorectal cancerpatients and gynecological cancer patients. For some applications, thePBMC samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table P. Alternatively, the PBMC samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table P.

TABLE P Breast vs. Colorectal Breast vs. Gynecological Colorectal vs.Gynecological Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4) Wavenumber(cm−1 ± 4) 704.9 731.4 1264.6 1546.6 707.7 954.1 1303.6 1528.3 753.1737.6 1309.4 1552.4 736.7 986.9 1313.8 1534.6 879.9 753.5 1365.4 1559.6764.6 999.4 1365.8 1541.3 939.2 767.5 1371.1 1568.3 776.7 1008.1 1371.61546.6 956.0 784.9 1378.4 1574.6 783.9 1028.4 1377.4 1551.9 990.7 805.11384.6 1589.1 788.7 1037.0 1384.6 1568.3 1008.1 928.1 1405.9 1605.4806.1 1051.5 1403.9 1574.1 1035.1 955.6 1414.0 1615.6 812.8 1067.91414.0 1578.5 1049.6 999.4 1427.1 1631.0 820.1 1083.3 1425.6 1590.01066.0 1030.3 1437.2 1637.3 836.5 1128.2 1435.7 1605.0 1072.7 1039.01452.6 1642.1 850.0 1153.2 1443.5 1611.7 1102.6 1067.4 1458.9 1645.5864.0 1161.4 1453.1 1626.7 1172.5 1126.2 1465.6 1648.4 870.2 1170.11459.8 1642.1 1221.2 1162.9 1474.3 1654.6 880.3 1179.3 1467.1 1648.41401.5 1170.1 1501.8 1660.9 887.1 1186.5 1474.8 1660.4 1568.8 1178.31506.1 1664.7 898.2 1202.9 1498.4 1673.9 1186.0 1511.9 1694.6 920.41252.1 1501.8 1693.7 1202.9 1528.3 1698.5 927.6 1262.7 1507.1 1700.91219.8 1532.2 939.6 1275.7 1512.4 1728.4 1251.1 1540.8 946.4 1299.81516.7 1734.7

For some applications, one, two, three, or more of the followingwavenumbers selected from Table P are used to differentiate betweenbreast cancer patients and colorectal cancer patients: 879.9±4 cm-1,939.2±4 cm-1, 1035.1±4 cm-1, 1066.0±4 cm-1, 1172.5±4 cm-1, 1568.8±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table P are used to differentiate betweenbreast cancer patients and gynecological cancer patients: 1162.9±4 cm-1,1186.0±4 cm-1, 1251.1±4 cm-1, 1365.4±4 cm-1, 1465.6±4 cm-1, 1528.3±4cm-1 and 1648.4±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table P are used to differentiate betweencolorectal cancer patients and gynecological cancer patients: 954.1±4cm-1, 1037.0±4 cm-1, 1067.9±4 cm-1, 1170.1±4 cm-1, 1365.8±4 cm-1 and1384.6±4 cm-1.

FIG. 12B shows statistical analysis and P values of FTIR-MSP spectraobtained from plasma samples of breast cancer patients, gynecologicalcancer patients and colorectal cancer patients (GI). As shown, someapplications of the present invention distinguish between

-   -   a) Breast cancer patients and colorectal cancer patients;    -   b) Breast cancer patients and gynecological cancer patients; and    -   c) Colorectal cancer patients and gynecological cancer patients.

Table Q lists wavenumbers that were identified in the set of experimentsas presented in FIG. 12B. Typically, plasma samples were analyzed byFTIR-MSP techniques using these wavenumbers to distinguish between: a)breast cancer patients and colorectal cancer patients; b) breast cancerpatients and gynecological cancer patients, and c) colorectal cancerpatients and gynecological cancer patients. For some applications, theplasma samples are analyzed by FTIR-MSP at at least one wavenumberselected from Table Q. Alternatively, the plasma samples are analyzed byFTIR-MSP at at least two or three wavenumbers selected from Table Q.

TABLE Q Breast vs. Colorectal Breast vs. Gynecological Colorectal vs.Gynecological Wavenumber (cm−1 ± 4) Wavenumber (cm−1 ± 4) Wavenumber(cm−1 ± 4) 716.9 1115.1 715.0 1164.8 1528.3 739.1 1116.1 1496.5 1712.0728.5 1142.1 728.0 1171.1 1534.6 773.3 1138.3 1501.3 1719.7 742.0 1156.1756.0 1177.3 1552.4 795.0 1175.9 1511.4 1734.7 796.5 1174.4 762.2 1193.71565.9 823.0 1193.2 1519.6 1740.9 823.0 1199.5 821.5 1204.8 1579.4 833.61201.9 1528.3 1749.1 831.2 1249.6 829.2 1217.3 1587.6 847.1 1241.91535.5 1756.4 883.2 1271.3 836.5 1229.9 1591.5 856.7 1257.8 1542.31767.4 904.5 1282.4 846.6 1238.1 1610.8 876.0 1271.8 1552.4 948.3 1370.7856.7 1315.2 1615.1 940.6 1284.8 1565.9 955.6 1379.8 876.0 1335.9 1630.5955.1 1295.9 1578.0 975.3 1464.7 882.3 1388.5 1641.1 962.3 1304.1 1587.61003.8 1573.1 904.9 1412.6 1647.9 976.8 1322.9 1615.1 1010.5 1609.3919.4 1421.3 1653.7 987.9 1336.4 1626.7 1030.8 1634.4 927.1 1436.71660.9 998.5 1360.1 1631.0 1039.0 1661.9 937.7 1448.8 1667.6 1009.61389.5 1635.3 1050.1 1666.2 948.3 1459.4 1694.2 1017.3 1412.1 1642.11070.8 1740.4 961.3 1467.1 1701.9 1028.4 1426.6 1647.9 1080.4 1745.3980.1 1473.8 1735.1 1047.6 1437.2 1654.1 1090.5 1751.0 1005.2 1479.61748.2 1056.8 1448.8 1659.9 1099.7 1790.1 1018.7 1497.0 1756.8 1062.11458.9 1667.2 1106.0 1039.9 1501.3 1778.0 1071.3 1466.1 1678.7 1055.81506.1 1783.4 1082.8 1473.3 1685.0 1144.1 1511.9 1098.7 1479.6 1693.71157.1 1521.1 1107.4 1484.9 1701.9

For some applications, one, two, three, or more of the followingwavenumbers selected from Table Q are used to differentiate betweenbreast cancer patients and colorectal cancer patients: 823.0±4 cm-1,904.5±4 cm-1, 955.6±4 cm-1, 1003.8±4 cm-1, 1039.0±4 cm-1, 1099.7±4 cm-1,and 1174.4±4 cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table Q are used to differentiate betweenbreast cancer patients and gynecological cancer patients: 961.3±4 cm-1,1005.2±4 cm-1, 1039.9±4 cm-1, 1055.8±4 cm-1, 1528.3±4 cm-1, and 1647.9±4cm-1.

For some applications, one, two, three, or more of the followingwavenumbers selected from Table Q are used to differentiate betweencolorectal cancer patients and gynecological cancer patients: 955.1±4cm-1, 1028.4±4 cm-1, 1047.6±4 cm-1, 1098.7±4 cm-1, 1175.9±4 cm-11535.5±4 cm-1, and 1647.9±4 cm-1.

Reference is made to FIGS. 13A-D, which are graphs representing thesecond derivative of FTIR absorption spectra, and analysis thereof,based on PBMC (FIG. 13A) and plasma (FIG. 13B) samples from cancerpatients and healthy controls, derived in accordance with someapplications of the present invention. As shown in FIGS. 13A-B, thesecond derivative spectral analysis shows that PBMC and plasma samplesfrom cancer patients differed from the spectra of healthy control. Mainspectral regions are marked.

Table R lists wavenumbers that were identified for diagnosis of cancerusing PBMC samples with reference to the set of experiments as presentedin FIG. 13A-D.

TABLE R Wavenumber (cm−1 ± 4) 706.3 1117.1 1420.8 1562.5 742.9 1134.91431.4 1566.9 749.7 1146.5 1437.2 1569.3 841.8 1162.4 1453.6 1579.4900.1 1188.4 1470.9 1587.1 910.7 1200.5 1476.7 1598.7 942.5 1220.71485.4 1613.6 956.5 1228.1 1496.0 1623.3 977.7 1276.6 1499.4 1628.1993.6 1285.3 1504.2 1643.1 1034.1 1292.1 1510.0 1649.8 1048.1 1298.81514.3 1663.3 1059.7 1321.0 1523.0 1669.6 1071.3 1369.2 1529.8 1675.81079.0 1382.2 1538.0 1681.6 1094.9 1389.5 1544.2 1699.5 1110.3 1403.91555.8 1709.6

For some applications, one, two, three, or more of the followingwavenumbers selected from Table R are used to diagnose cancer using PBMCsamples: 749.70±4 cm-1, 841.8±4 cm-1, 993.6±4 cm-1, 1034.1±4 cm-1,1117.1±4 cm-1, 1146.5±4 cm-1, 1228.1±4 cm-1 and 1276.6±4 cm-1.

Table S lists wavenumbers that were identified for diagnosis of cancerusing plasma samples with reference to the set of experiments aspresented in FIG. 13A-D.

TABLE S 733.3 959.4 1174.0 1399.1 1562.5 748.2 963.8 1180.7 1414.51577.5 753.5 971.9 1199.5 1421.3 1584.2 771.4 979.7 1217.3 1429.5 1601.6779.1 989.8 1227.5 1448.8 1627.1 799.3 994.6 1233.7 1454.1 1643.1 821.51008.1 1263.6 1460.8 1651.3 821.5 1014.4 1278.1 1484.9 1666.2 827.81038.0 1289.7 1490.7 1675.8 840.3 1054.9 1295.0 1499.4 1681.6 846.61066.9 1307.5 1504.2 1687.4 858.6 1074.6 1321.5 1510.0 1694.2 870.21088.6 1331.6 1515.3 1707.2 889.0 1111.3 1339.8 1519.2 1717.8 897.21128.6 1352.3 1523.0 1733.2 913.6 1136.8 1364.4 1529.8 1739.5 923.71146.0 1378.9 1537.5 1758.3 938.7 1153.7 1384.6 1544.2 1769.4 948.31160.9 1392.4 1555.8

For some applications, one, two, three, or more of the followingwavenumbers selected from Table S are used to diagnose cancer usingplasma samples: 846.6±4 cm-1, 1008.1±4 cm-1, 1038.0±4 cm-1, 1111.3±4cm-1, 1153.7±4 cm-1, 1278.1±4 cm-1, and 1289.7±4 cm-1.

FIGS. 14A-C show receiver operating characteristic (ROC) curve analysis,including the area under the curve (AUC), of PBMC (FIG. 14A) and plasma(FIG. 14B) of healthy controls, compared to the subjects with malignanttumors (cancer patients). As shown, combined use of both the plasma andPBMC samples (FIG. 14C) increased sensitivity and specificity for thediagnosis of cancer.

FIGS. 15A-D are schematic illustrations of slides containing abiological plasma sample that was air dried for 0.5 h under laminar flowat a temperature of 30±4 C (FIGS. 15A-B) to remove water in accordancewith some applications of the present invention, compared to slidescontaining a biological plasma sample that was air dried for 0.5 h underlaminar flow at a temperature of 21 C to remove water (FIG. 15C-D).Results show that drying at a temperature of 30±4 C produces improvedslides, for use in applications of the present invention. It is notedthat FIGS. 15B and 15D are at the same microscopic zoom level and are anenlarged view of FIGS. 15A and 15C respectively.

It is noted that the scope of the present invention includes the use ofonly one wavenumber biomarker for differential diagnosis of benign andmalignant solid tumors, as well as the use of two, three, four, or morewavenumbers.

Embodiments of the present invention described herein can take the formof an entirely hardware embodiment, an entirely software embodiment oran embodiment including both hardware and software elements. In anembodiment, the invention is implemented in software, which includes butis not limited to firmware, resident software, microcode, etc.

Furthermore, the embodiments of the invention can take the form of acomputer program product accessible from a computer-usable orcomputer-readable medium providing program code for use by or inconnection with a computer or any instruction execution system. For thepurposes of this description, a computer-usable or computer readablemedium can be any apparatus that can comprise, store, communicate,propagate, or transport the program for use by or in connection with theinstruction execution system, apparatus, or device. The medium can be anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system (or apparatus or device) or a propagation medium.

Examples of a computer-readable medium include a semiconductor or solidstate memory, magnetic tape, a removable computer diskette, a randomaccess memory (RAM), a read-only memory (ROM), a rigid magnetic disk andan optical disk. Current examples of optical disks include compactdisk-read only memory (CD-ROM), compact disk-read/write (CD-R/W) andDVD.

Reference is made to FIG. 16. Typically, the operations described hereinare performed by a system 30 which transforms the physical state of amemory 26, which is a real physical article, to have a differentmagnetic polarity, electrical charge, or the like depending on thetechnology of the memory that is used. A processor 22 of system 30performs the analysis described herein, based on inputs from an FTIRsystem 20, and outputs the results of the analysis to an output device24 (e.g., a screen, a printer, or a long-term storage medium). System 30may thus be used to perform analysis that includes any of thewavenumbers described herein.

A data processing system suitable for storing and/or executing programcode will include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code in order to reduce the number of times code must beretrieved from bulk storage during execution. The system can read theinventive instructions on the program storage devices and follow theseinstructions to execute the methodology of the embodiments of theinvention.

Input/output (I/O) devices (including but not limited to keyboards,displays, pointing devices, etc.) can be coupled to the system eitherdirectly or through intervening I/O controllers. Network adapters mayalso be coupled to the system to enable the data processing system tobecome coupled to other data processing systems or remote printers orstorage devices through intervening private or public networks. Modems,cable modem and Ethernet cards are just a few of the currently availabletypes of network adapters.

Computer program code for carrying out operations of the presentinvention may be written in any combination of one or more programminglanguages, including an object oriented programming language such asJava, Smalltalk, C++ or the like and conventional procedural programminglanguages, such as the C programming language or similar programminglanguages.

It will be understood that the operations described herein can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor (e.g., processor 22) of ageneral purpose computer, special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means forimplementing the functions/acts described herein. These computer programinstructions may also be stored in a computer-readable medium that candirect a computer or other programmable data processing apparatus tofunction in a particular manner, such that the instructions stored inthe computer-readable medium produce an article of manufacture includinginstruction means which implement the functions/acts described herein.The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions which execute on the computer or other programmableapparatus provide processes for implementing the functions/actsdescribed herein.

It will be appreciated by persons skilled in the art that the presentinvention is not limited to what has been particularly shown anddescribed hereinabove. Rather, the scope of the present inventionincludes both combinations and subcombinations of the various featuresdescribed hereinabove, as well as variations and modifications thereofthat are not in the prior art, which would occur to persons skilled inthe art upon reading the foregoing description.

The invention claimed is:
 1. A method comprising: identifying a subject as possibly having a benign tumor in ovarian tissue of the subject; isolating a Peripheral Blood Mononuclear Cells (PBMC) sample from a peripheral blood sample of the subject; obtaining an infrared (IR) spectrum of the Peripheral Blood Mononuclear Cells (PBMC) sample of the subject by analyzing the sample by infrared spectroscopy; assessing a characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 754.0±4 cm-1, 1103.6±4 cm-1, 1121.4±4 cm-1, 1346.1±4 cm-1, 1376.9±4 cm-1, 753.50±4 cm-1, 850.5±4 cm-1, 918.9±4 cm-1, 1058.7±4 cm-1, 1187.9±4 cm-1 and 1651.7±4 cm-1; and using a processor comparing, at the at least one wavenumber, the infrared spectrum to an infrared spectrum obtained from a PBMC sample from a person without a benign tumor, to detect a difference between the infrared spectrum of the PBMC sample of the subject and the infrared spectrum obtained from the PBMC sample from the person without a benign tumor.
 2. The method according to claim 1, further comprising: isolating a blood plasma sample from a peripheral blood sample of the subject; obtaining an infrared (IR) spectrum of the plasma sample of the subject by analyzing the plasma sample by infrared spectroscopy; assessing a characteristic of the plasma sample corresponding to at least one plasma wavenumber selected from the group consisting of: 830.7±4 cm-1, 1007.6±4 cm-1, 1290.1±4 cm-1, 1676.8±4 cm-1, 1716.3±4 cm-1, 1754.9±4 cm-1, 777.2±4 cm-1, 1039.4±4 cm-1, 1052.5±4 cm-1, 1156.1±4 cm-1, 1218.3±4 cm-1 and 1369.2±4 cm-1; and comparing, at the at least one plasma wavenumber, the infrared spectrum of the plasma sample to an infrared spectrum obtained from a plasma sample from a person without a benign tumor, to detect a difference between the infrared spectrum of the plasma sample of the subject and the infrared spectrum obtained from the plasma sample from the person without a benign tumor.
 3. The method according to claim 1, wherein analyzing comprises assessing the characteristic corresponding to at least two wavenumbers selected from the group.
 4. The method according to claim 1, wherein analyzing comprises assessing the characteristic corresponding to at least three wavenumbers selected from the group.
 5. The method according to claim 1, wherein analyzing the sample comprises obtaining a second derivative of the infrared (IR) spectrum of the sample.
 6. A method comprising: identifying a subject as possibly having a benign tumor in ovarian tissue of the subject; isolating a blood plasma sample from a peripheral blood sample of the subject; obtaining an infrared (IR) spectrum of the plasma blood sample of the subject by analyzing the sample by infrared spectroscopy; assessing a characteristic of the sample corresponding to at least one plasma wavenumber selected from the group consisting of: 830.7±4 cm-1, 1007.6±4 cm-1, 1290.1±4 cm-1, 1676.8±4 cm-1, 1716.3±4 cm-1, 1754.9±4 cm-1, 777.2±4 cm-1, 1039.4±4 cm-1, 1052.5±4 cm-1, 1156.1±4 cm-1, 1218.3±4 cm-1 and 1369.2±4 cm-1; and using a processor comparing, at the at least one plasma wavenumber, the infrared spectrum to an infrared spectrum obtained from a plasma blood sample from a person without a benign tumor, to detect a difference between the infrared spectrum of the plasma blood sample of the subject and the infrared spectrum obtained from the plasma blood sample from the person without a benign tumor.
 7. A method comprising: obtaining an infrared (IR) spectrum of a blood plasma sample isolated from a peripheral blood sample taken from a subject exhibiting a clinical parameter that may trigger a false positive diagnosis of a malignant condition in gynecological tissue selected from the group consisting of: ovarian tissue, endometrial tissue, and cervical tissue, by analyzing the sample by infrared spectroscopy; assessing a characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 740.0±4 cm-1, 971.0±4 cm-1, 1019.7±4 cm-1, 1064.5±4 cm-1, 1291.1±4 cm-1, 1378.4±4 cm-1; and using a processor, comparing, at the at least one wavenumber, the infrared spectrum to an infrared spectrum obtained from a blood plasma sample from a person without a malignant condition, to detect a difference between the infrared spectrum of the blood plasma sample of the subject and the infrared spectrum obtained from the blood plasma sample from the person without a malignant condition.
 8. The method according to claim 7, wherein the subject exhibiting a clinical parameter that may trigger a false positive diagnosis of a malignant condition includes a pregnant woman, and wherein obtaining the infrared (IR) spectrum of the blood plasma sample from the subject exhibiting a clinical parameter, comprises obtaining the infrared (IR) spectrum of the blood plasma sample from the pregnant woman.
 9. The method according to claim 1, wherein assessing the characteristic of the sample corresponding to at least one wavenumber comprises assessing the characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 754.0±4 cm-1, 1103.6±4 cm-1, 1121.4±4 cm-1, 1346.1±4 cm-1, and 1376.9±4 cm-1, and wherein the person without a benign tumor is a person without a tumor.
 10. The method according to claim 1, wherein assessing the characteristic of the sample corresponding to at least one wavenumber comprises assessing the characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 753.50±4 cm-1, 850.5±4 cm-1, 918.9±4 cm-1, 1058.7±4 cm-1, 1187.9±4 cm-1 and 1651.7±4 cm-1, and wherein the person without a benign tumor is a person with a malignant tumor.
 11. The method according to claim 6, wherein assessing the characteristic of the sample corresponding to at least one wavenumber comprises assessing the characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 830.7±4 cm-1, 1007.6±4 cm-1, 1290.1±4 cm-1, 1676.8±4 cm-1, 1716.3±4 cm-1, and 1754.9±4 cm-1, and wherein the person without a benign tumor is a person without a tumor.
 12. The method according to claim 6, wherein assessing the characteristic of the sample corresponding to at least one wavenumber comprises assessing the characteristic of the sample corresponding to at least one wavenumber selected from the group consisting of: 777.2±4 cm-1, 1039.4±4 cm-1, 1052.5±4 cm-1, 1156.1±4 cm-1, 1218.3±4 cm-1 and 1369.2±4 cm-1, and wherein the person without a benign tumor is a person with a malignant tumor. 